Overview

Dataset statistics

Number of variables203
Number of observations73663
Missing cells241828
Missing cells (%)1.6%
Total size in memory98.8 MiB
Average record size in memory1.4 KiB

Variable types

Text9
Categorical33
Numeric161

Alerts

TIPO has constant value ""Constant
NIVEL has constant value ""Constant
SUBNIVEL has constant value ""Constant
V109 has constant value ""Constant
V137 has constant value ""Constant
V139 has constant value ""Constant
CV_MUN has a high cardinality: 436 distinct valuesHigh cardinality
C_NOM_MUN has a high cardinality: 2049 distinct valuesHigh cardinality
CV_LOC has a high cardinality: 640 distinct valuesHigh cardinality
CV_LOC is highly imbalanced (54.9%)Imbalance
CV_CARACTERIZAN2 is highly imbalanced (53.5%)Imbalance
C_CARACTERIZAN2 is highly imbalanced (53.5%)Imbalance
CV_MODALIDAD is highly imbalanced (65.7%)Imbalance
C_MODALIDAD is highly imbalanced (65.7%)Imbalance
CV_OPCION_EDUCATIVA is highly imbalanced (76.6%)Imbalance
C_OPCION_EDUCATIVA is highly imbalanced (78.3%)Imbalance
CV_PLAN_ESTUDIO is highly imbalanced (89.2%)Imbalance
CV_DURACION is highly imbalanced (70.1%)Imbalance
C_DURACION is highly imbalanced (70.1%)Imbalance
CV_ESTATUS is highly imbalanced (85.6%)Imbalance
C_CARRERA_ESTATUS is highly imbalanced (85.6%)Imbalance
CV_MOTIVO is highly imbalanced (85.5%)Imbalance
C_MOTIVO has 68757 (93.3%) missing valuesMissing
E3 has 50232 (68.2%) missing valuesMissing
E4 has 50627 (68.7%) missing valuesMissing
E19 has 71516 (97.1%) missing valuesMissing
V7 is highly skewed (γ1 = 77.2907752)Skewed
V17 is highly skewed (γ1 = 21.1230925)Skewed
V21 is highly skewed (γ1 = 106.5510594)Skewed
V22 is highly skewed (γ1 = 122.8182518)Skewed
V23 is highly skewed (γ1 = 116.7147387)Skewed
V24 is highly skewed (γ1 = 154.9180114)Skewed
V25 is highly skewed (γ1 = 132.7308829)Skewed
V26 is highly skewed (γ1 = 47.89725896)Skewed
V27 is highly skewed (γ1 = 141.3762919)Skewed
V28 is highly skewed (γ1 = 105.4429085)Skewed
V29 is highly skewed (γ1 = 122.215758)Skewed
V30 is highly skewed (γ1 = 116.5077145)Skewed
V31 is highly skewed (γ1 = 146.6808782)Skewed
V32 is highly skewed (γ1 = 102.8602683)Skewed
V33 is highly skewed (γ1 = 36.99023399)Skewed
V34 is highly skewed (γ1 = 131.9587464)Skewed
V35 is highly skewed (γ1 = 95.69209715)Skewed
V36 is highly skewed (γ1 = 135.1893143)Skewed
V37 is highly skewed (γ1 = 120.9642124)Skewed
V38 is highly skewed (γ1 = 176.5290489)Skewed
V39 is highly skewed (γ1 = 73.206341)Skewed
V40 is highly skewed (γ1 = 35.75917761)Skewed
V41 is highly skewed (γ1 = 158.5197772)Skewed
V42 is highly skewed (γ1 = 74.80228687)Skewed
V43 is highly skewed (γ1 = 83.00557817)Skewed
V44 is highly skewed (γ1 = 74.83527223)Skewed
V45 is highly skewed (γ1 = 250.5504628)Skewed
V46 is highly skewed (γ1 = 108.5803543)Skewed
V47 is highly skewed (γ1 = 270.4297199)Skewed
V48 is highly skewed (γ1 = 69.47791048)Skewed
V49 is highly skewed (γ1 = 98.66195382)Skewed
V50 is highly skewed (γ1 = 119.6530082)Skewed
V51 is highly skewed (γ1 = 112.0675243)Skewed
V52 is highly skewed (γ1 = 139.8181859)Skewed
V53 is highly skewed (γ1 = 92.23406543)Skewed
V54 is highly skewed (γ1 = 40.4710382)Skewed
V55 is highly skewed (γ1 = 139.8882091)Skewed
V56 is highly skewed (γ1 = 78.60462431)Skewed
V57 is highly skewed (γ1 = 100.142229)Skewed
V58 is highly skewed (γ1 = 90.62407044)Skewed
V59 is highly skewed (γ1 = 159.3018771)Skewed
V60 is highly skewed (γ1 = 74.39331204)Skewed
V61 is highly skewed (γ1 = 33.31947359)Skewed
V62 is highly skewed (γ1 = 114.9922679)Skewed
V63 is highly skewed (γ1 = 125.5990689)Skewed
V64 is highly skewed (γ1 = 122.5245842)Skewed
V65 is highly skewed (γ1 = 153.1126722)Skewed
V66 is highly skewed (γ1 = 85.47001114)Skewed
V67 is highly skewed (γ1 = 38.89918628)Skewed
V68 is highly skewed (γ1 = 112.0891606)Skewed
V69 is highly skewed (γ1 = 137.0960307)Skewed
V70 is highly skewed (γ1 = 128.9884415)Skewed
V71 is highly skewed (γ1 = 186.5471315)Skewed
V72 is highly skewed (γ1 = 64.84295709)Skewed
V73 is highly skewed (γ1 = 34.39427615)Skewed
V74 is highly skewed (γ1 = 81.77091896)Skewed
V75 is highly skewed (γ1 = 89.76022534)Skewed
V76 is highly skewed (γ1 = 81.05494573)Skewed
V77 is highly skewed (γ1 = 271.409285)Skewed
V78 is highly skewed (γ1 = 112.8912979)Skewed
V79 is highly skewed (γ1 = 270.4297199)Skewed
V80 is highly skewed (γ1 = 84.97010965)Skewed
V81 is highly skewed (γ1 = 108.7216518)Skewed
V82 is highly skewed (γ1 = 100.2947882)Skewed
V83 is highly skewed (γ1 = 134.0654979)Skewed
V84 is highly skewed (γ1 = 52.56039421)Skewed
V85 is highly skewed (γ1 = 37.82804639)Skewed
V86 is highly skewed (γ1 = 124.7039165)Skewed
V87 is highly skewed (γ1 = 134.7250736)Skewed
V88 is highly skewed (γ1 = 130.6349669)Skewed
V89 is highly skewed (γ1 = 153.1612378)Skewed
V90 is highly skewed (γ1 = 157.1705447)Skewed
V91 is highly skewed (γ1 = 96.30295992)Skewed
V92 is highly skewed (γ1 = 92.78838341)Skewed
V93 is highly skewed (γ1 = 111.9702015)Skewed
V94 is highly skewed (γ1 = 103.6400093)Skewed
V95 is highly skewed (γ1 = 133.4660058)Skewed
V96 is highly skewed (γ1 = 118.5558924)Skewed
V97 is highly skewed (γ1 = 38.78293331)Skewed
V98 is highly skewed (γ1 = 45.53483631)Skewed
V99 is highly skewed (γ1 = 96.68341085)Skewed
V100 is highly skewed (γ1 = 66.27977742)Skewed
V101 is highly skewed (γ1 = 93.88544366)Skewed
V102 is highly skewed (γ1 = 75.93972971)Skewed
V103 is highly skewed (γ1 = 28.65502947)Skewed
V104 is highly skewed (γ1 = 142.3579164)Skewed
V105 is highly skewed (γ1 = 210.8436693)Skewed
V106 is highly skewed (γ1 = 173.1711623)Skewed
V107 is highly skewed (γ1 = 249.316863)Skewed
V108 is highly skewed (γ1 = 241.5068079)Skewed
V110 is highly skewed (γ1 = 111.7388453)Skewed
V111 is highly skewed (γ1 = 129.4923111)Skewed
V112 is highly skewed (γ1 = 122.6201765)Skewed
V113 is highly skewed (γ1 = 147.0145832)Skewed
V114 is highly skewed (γ1 = 139.0031722)Skewed
V115 is highly skewed (γ1 = 61.60426835)Skewed
V116 is highly skewed (γ1 = 22.17805949)Skewed
V117 is highly skewed (γ1 = 38.25359741)Skewed
V118 is highly skewed (γ1 = 29.21611173)Skewed
V119 is highly skewed (γ1 = 63.27149111)Skewed
V120 is highly skewed (γ1 = 55.61048776)Skewed
V121 is highly skewed (γ1 = 30.69952854)Skewed
V122 is highly skewed (γ1 = 124.9046904)Skewed
V123 is highly skewed (γ1 = 150.0369022)Skewed
V124 is highly skewed (γ1 = 140.4079598)Skewed
V125 is highly skewed (γ1 = 116.0527116)Skewed
V126 is highly skewed (γ1 = 51.69694843)Skewed
V127 is highly skewed (γ1 = 52.62403919)Skewed
V128 is highly skewed (γ1 = 50.8004828)Skewed
V129 is highly skewed (γ1 = 41.1390851)Skewed
V130 is highly skewed (γ1 = 47.39155785)Skewed
V131 is highly skewed (γ1 = 40.37904456)Skewed
V132 is highly skewed (γ1 = 28.48076814)Skewed
V133 is highly skewed (γ1 = 30.19165243)Skewed
V134 is highly skewed (γ1 = 179.2318921)Skewed
V135 is highly skewed (γ1 = 141.7286591)Skewed
V136 is highly skewed (γ1 = 167.2002678)Skewed
V138 is highly skewed (γ1 = 265.6878691)Skewed
V140 is highly skewed (γ1 = 60.18857148)Skewed
V141 is highly skewed (γ1 = 82.32078966)Skewed
V142 is highly skewed (γ1 = 70.88176582)Skewed
V143 is highly skewed (γ1 = 80.48784059)Skewed
V144 is highly skewed (γ1 = 32.21362872)Skewed
V145 is highly skewed (γ1 = 32.96285914)Skewed
V149 is highly skewed (γ1 = 44.30923617)Skewed
V151 is highly skewed (γ1 = 29.72425342)Skewed
V155 is highly skewed (γ1 = 74.42833409)Skewed
V157 is highly skewed (γ1 = 59.10580381)Skewed
V158 is highly skewed (γ1 = 28.54705464)Skewed
V159 is highly skewed (γ1 = 29.42979686)Skewed
V160 is highly skewed (γ1 = 29.12622102)Skewed
V161 is highly skewed (γ1 = 47.07820276)Skewed
N_EXTNUM has 45891 (62.3%) zerosZeros
V1 has 50232 (68.2%) zerosZeros
V2 has 29983 (40.7%) zerosZeros
V5 has 51387 (69.8%) zerosZeros
V6 has 51387 (69.8%) zerosZeros
V7 has 51387 (69.8%) zerosZeros
V8 has 44429 (60.3%) zerosZeros
V9 has 34474 (46.8%) zerosZeros
V10 has 5261 (7.1%) zerosZeros
V11 has 5262 (7.1%) zerosZeros
V12 has 5261 (7.1%) zerosZeros
V13 has 5262 (7.1%) zerosZeros
V14 has 60520 (82.2%) zerosZeros
V15 has 23659 (32.1%) zerosZeros
V16 has 70344 (95.5%) zerosZeros
V17 has 73499 (99.8%) zerosZeros
V18 has 71872 (97.6%) zerosZeros
V20 has 8983 (12.2%) zerosZeros
V21 has 9986 (13.6%) zerosZeros
V22 has 10039 (13.6%) zerosZeros
V23 has 9366 (12.7%) zerosZeros
V24 has 67676 (91.9%) zerosZeros
V25 has 65897 (89.5%) zerosZeros
V26 has 60172 (81.7%) zerosZeros
V27 has 9364 (12.7%) zerosZeros
V28 has 10325 (14.0%) zerosZeros
V29 has 10199 (13.8%) zerosZeros
V30 has 9492 (12.9%) zerosZeros
V31 has 68197 (92.6%) zerosZeros
V32 has 65979 (89.6%) zerosZeros
V33 has 61751 (83.8%) zerosZeros
V34 has 9491 (12.9%) zerosZeros
V35 has 16915 (23.0%) zerosZeros
V36 has 16781 (22.8%) zerosZeros
V37 has 16119 (21.9%) zerosZeros
V38 has 69076 (93.8%) zerosZeros
V39 has 66306 (90.0%) zerosZeros
V40 has 64193 (87.1%) zerosZeros
V41 has 16117 (21.9%) zerosZeros
V42 has 73591 (99.9%) zerosZeros
V43 has 73592 (99.9%) zerosZeros
V44 has 73590 (99.9%) zerosZeros
V45 has 73661 (> 99.9%) zerosZeros
V46 has 73650 (> 99.9%) zerosZeros
V47 has 73658 (> 99.9%) zerosZeros
V48 has 73590 (99.9%) zerosZeros
V49 has 7013 (9.5%) zerosZeros
V50 has 7090 (9.6%) zerosZeros
V51 has 6786 (9.2%) zerosZeros
V52 has 63667 (86.4%) zerosZeros
V53 has 64616 (87.7%) zerosZeros
V54 has 54781 (74.4%) zerosZeros
V55 has 7730 (10.5%) zerosZeros
V56 has 10738 (14.6%) zerosZeros
V57 has 10492 (14.2%) zerosZeros
V58 has 9698 (13.2%) zerosZeros
V59 has 68419 (92.9%) zerosZeros
V60 has 66254 (89.9%) zerosZeros
V61 has 61769 (83.9%) zerosZeros
V62 has 10901 (14.8%) zerosZeros
V63 has 10488 (14.2%) zerosZeros
V64 has 9683 (13.1%) zerosZeros
V65 has 68842 (93.5%) zerosZeros
V66 has 66308 (90.0%) zerosZeros
V67 has 63099 (85.7%) zerosZeros
V68 has 17294 (23.5%) zerosZeros
V69 has 16969 (23.0%) zerosZeros
V70 has 16234 (22.0%) zerosZeros
V71 has 69446 (94.3%) zerosZeros
V72 has 66523 (90.3%) zerosZeros
V73 has 64931 (88.1%) zerosZeros
V74 has 73594 (99.9%) zerosZeros
V75 has 73595 (99.9%) zerosZeros
V76 has 73593 (99.9%) zerosZeros
V77 has 73662 (> 99.9%) zerosZeros
V78 has 73650 (> 99.9%) zerosZeros
V79 has 73658 (> 99.9%) zerosZeros
V80 has 8169 (11.1%) zerosZeros
V81 has 8211 (11.1%) zerosZeros
V82 has 7895 (10.7%) zerosZeros
V83 has 65063 (88.3%) zerosZeros
V84 has 65028 (88.3%) zerosZeros
V85 has 56456 (76.6%) zerosZeros
V86 has 39956 (54.2%) zerosZeros
V87 has 43253 (58.7%) zerosZeros
V88 has 37786 (51.3%) zerosZeros
V89 has 71708 (97.3%) zerosZeros
V90 has 70684 (96.0%) zerosZeros
V91 has 69525 (94.4%) zerosZeros
V92 has 41313 (56.1%) zerosZeros
V93 has 44578 (60.5%) zerosZeros
V94 has 38879 (52.8%) zerosZeros
V95 has 71877 (97.6%) zerosZeros
V96 has 70751 (96.0%) zerosZeros
V97 has 70279 (95.4%) zerosZeros
V98 has 49602 (67.3%) zerosZeros
V99 has 52761 (71.6%) zerosZeros
V100 has 47403 (64.4%) zerosZeros
V101 has 72509 (98.4%) zerosZeros
V102 has 71566 (97.2%) zerosZeros
V103 has 71689 (97.3%) zerosZeros
V104 has 73648 (> 99.9%) zerosZeros
V105 has 73648 (> 99.9%) zerosZeros
V106 has 73646 (> 99.9%) zerosZeros
V107 has 73661 (> 99.9%) zerosZeros
V108 has 73660 (> 99.9%) zerosZeros
V109 has 73663 (100.0%) zerosZeros
V110 has 34757 (47.2%) zerosZeros
V111 has 37574 (51.0%) zerosZeros
V112 has 33122 (45.0%) zerosZeros
V113 has 70582 (95.8%) zerosZeros
V114 has 69624 (94.5%) zerosZeros
V115 has 67523 (91.7%) zerosZeros
V116 has 49912 (67.8%) zerosZeros
V117 has 52464 (71.2%) zerosZeros
V118 has 48328 (65.6%) zerosZeros
V119 has 72724 (98.7%) zerosZeros
V120 has 72131 (97.9%) zerosZeros
V121 has 72073 (97.8%) zerosZeros
V122 has 49906 (67.7%) zerosZeros
V123 has 52643 (71.5%) zerosZeros
V124 has 47950 (65.1%) zerosZeros
V125 has 72863 (98.9%) zerosZeros
V126 has 72142 (97.9%) zerosZeros
V127 has 72319 (98.2%) zerosZeros
V128 has 55291 (75.1%) zerosZeros
V129 has 57933 (78.6%) zerosZeros
V130 has 53686 (72.9%) zerosZeros
V131 has 73080 (99.2%) zerosZeros
V132 has 72518 (98.4%) zerosZeros
V133 has 72743 (98.8%) zerosZeros
V134 has 73652 (> 99.9%) zerosZeros
V135 has 73655 (> 99.9%) zerosZeros
V136 has 73651 (> 99.9%) zerosZeros
V137 has 73663 (100.0%) zerosZeros
V138 has 73661 (> 99.9%) zerosZeros
V139 has 73663 (100.0%) zerosZeros
V140 has 44668 (60.6%) zerosZeros
V141 has 46834 (63.6%) zerosZeros
V142 has 43485 (59.0%) zerosZeros
V143 has 72085 (97.9%) zerosZeros
V144 has 71505 (97.1%) zerosZeros
V145 has 70908 (96.3%) zerosZeros
V146 has 30469 (41.4%) zerosZeros
V147 has 28989 (39.4%) zerosZeros
V148 has 25690 (34.9%) zerosZeros
V149 has 72027 (97.8%) zerosZeros
V150 has 69442 (94.3%) zerosZeros
V151 has 69792 (94.7%) zerosZeros
V152 has 18972 (25.8%) zerosZeros
V153 has 19324 (26.2%) zerosZeros
V154 has 15185 (20.6%) zerosZeros
V155 has 71286 (96.8%) zerosZeros
V156 has 67956 (92.3%) zerosZeros
V157 has 68507 (93.0%) zerosZeros
V158 has 35409 (48.1%) zerosZeros
V159 has 38158 (51.8%) zerosZeros
V160 has 28781 (39.1%) zerosZeros
V161 has 72360 (98.2%) zerosZeros
V162 has 69639 (94.5%) zerosZeros

Reproduction

Analysis started2024-03-10 02:10:09.472378
Analysis finished2024-03-10 02:10:16.508858
Duration7.04 seconds
Software versionydata-profiling vv4.6.5
Download configurationconfig.json

Variables

CCT_INS_PLA
Text

Distinct16490
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:16.709061image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters736630
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique223 ?
Unique (%)0.3%

Sample

1st row01MMS0001E
2nd row01MMS0001E
3rd row01MMS0001E
4th row01MMS0001E
5th row01MMS0002D
ValueCountFrequency (%)
25mms0458l 40
 
0.1%
25mms0518j 38
 
0.1%
25mms0457m 34
 
< 0.1%
28mms0445e 32
 
< 0.1%
02mms0227j 28
 
< 0.1%
25mms0452r 28
 
< 0.1%
25mms0456n 27
 
< 0.1%
25mms0475b 27
 
< 0.1%
02mms0191l 26
 
< 0.1%
25mms0450t 25
 
< 0.1%
Other values (16480) 73358
99.6%
2024-03-09T21:10:17.256399image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 150130
20.4%
0 112898
15.3%
1 80161
10.9%
S 76450
10.4%
2 54236
 
7.4%
3 37896
 
5.1%
5 32629
 
4.4%
4 29864
 
4.1%
6 25259
 
3.4%
7 24242
 
3.3%
Other values (26) 112865
15.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 441978
60.0%
Uppercase Letter 294652
40.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 150130
51.0%
S 76450
25.9%
Z 5523
 
1.9%
J 2886
 
1.0%
F 2831
 
1.0%
E 2807
 
1.0%
L 2803
 
1.0%
X 2782
 
0.9%
Y 2764
 
0.9%
D 2751
 
0.9%
Other values (16) 42925
 
14.6%
Decimal Number
ValueCountFrequency (%)
0 112898
25.5%
1 80161
18.1%
2 54236
12.3%
3 37896
 
8.6%
5 32629
 
7.4%
4 29864
 
6.8%
6 25259
 
5.7%
7 24242
 
5.5%
8 23417
 
5.3%
9 21376
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 441978
60.0%
Latin 294652
40.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 150130
51.0%
S 76450
25.9%
Z 5523
 
1.9%
J 2886
 
1.0%
F 2831
 
1.0%
E 2807
 
1.0%
L 2803
 
1.0%
X 2782
 
0.9%
Y 2764
 
0.9%
D 2751
 
0.9%
Other values (16) 42925
 
14.6%
Common
ValueCountFrequency (%)
0 112898
25.5%
1 80161
18.1%
2 54236
12.3%
3 37896
 
8.6%
5 32629
 
7.4%
4 29864
 
6.8%
6 25259
 
5.7%
7 24242
 
5.5%
8 23417
 
5.3%
9 21376
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 736630
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 150130
20.4%
0 112898
15.3%
1 80161
10.9%
S 76450
10.4%
2 54236
 
7.4%
3 37896
 
5.1%
5 32629
 
4.4%
4 29864
 
4.1%
6 25259
 
3.4%
7 24242
 
3.3%
Other values (26) 112865
15.3%

NOMBRE_INS_PLA
Text

Distinct17391
Distinct (%)23.6%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:17.719262image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length105
Median length88
Mean length35.79288109
Min length4

Characters and Unicode

Total characters2636611
Distinct characters70
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3106 ?
Unique (%)4.2%

Sample

1st rowCENTRO DE ESTUDIOS DE BACHILLERATO 8/4 FRIDA KAHLO
2nd rowCENTRO DE ESTUDIOS DE BACHILLERATO 8/4 FRIDA KAHLO
3rd rowCENTRO DE ESTUDIOS DE BACHILLERATO 8/4 FRIDA KAHLO
4th rowCENTRO DE ESTUDIOS DE BACHILLERATO 8/4 FRIDA KAHLO
5th rowCENTRO DE ESTUDIOS DE BACHILLERATO 8/5 EZEQUIEL A. CHAVEZ
ValueCountFrequency (%)
de 27691
 
8.1%
telebachillerato 18857
 
5.5%
comunitario 13171
 
3.8%
num 10732
 
3.1%
preparatoria 10093
 
2.9%
colegio 9187
 
2.7%
centro 7873
 
2.3%
plantel 6028
 
1.8%
instituto 5886
 
1.7%
escuela 5532
 
1.6%
Other values (8562) 228134
66.5%
2024-03-09T21:10:18.472159image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 290573
11.0%
270035
10.2%
E 262597
10.0%
O 197760
 
7.5%
I 197647
 
7.5%
L 180463
 
6.8%
R 157180
 
6.0%
T 156821
 
5.9%
C 145508
 
5.5%
N 127290
 
4.8%
Other values (60) 650737
24.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2277444
86.4%
Space Separator 270035
 
10.2%
Decimal Number 54246
 
2.1%
Other Punctuation 31458
 
1.2%
Open Punctuation 1261
 
< 0.1%
Close Punctuation 1251
 
< 0.1%
Dash Punctuation 878
 
< 0.1%
Private Use 9
 
< 0.1%
Control 9
 
< 0.1%
Lowercase Letter 8
 
< 0.1%
Other values (3) 12
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 290573
12.8%
E 262597
11.5%
O 197760
8.7%
I 197647
8.7%
L 180463
 
7.9%
R 157180
 
6.9%
T 156821
 
6.9%
C 145508
 
6.4%
N 127290
 
5.6%
U 88486
 
3.9%
Other values (24) 473119
20.8%
Other Punctuation
ValueCountFrequency (%)
. 22832
72.6%
, 4436
 
14.1%
" 3755
 
11.9%
/ 224
 
0.7%
? 104
 
0.3%
' 75
 
0.2%
¿ 21
 
0.1%
@ 4
 
< 0.1%
; 3
 
< 0.1%
‰ 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 10249
18.9%
2 8018
14.8%
0 6255
11.5%
3 5650
10.4%
4 4758
8.8%
8 4332
8.0%
6 4263
7.9%
5 4065
 
7.5%
7 3396
 
6.3%
9 3260
 
6.0%
Control
ValueCountFrequency (%)
“ 6
66.7%
‰ 2
 
22.2%
‘ 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 1259
99.8%
[ 2
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
ż 7
87.5%
ş 1
 
12.5%
Initial Punctuation
ValueCountFrequency (%)
“ 5
83.3%
‘ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
270035
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1251
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 878
100.0%
Private Use
ValueCountFrequency (%)
9
100.0%
Other Letter
ValueCountFrequency (%)
º 3
100.0%
Currency Symbol
ValueCountFrequency (%)
¤ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2277455
86.4%
Common 359147
 
13.6%
Unknown 9
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 290573
12.8%
E 262597
11.5%
O 197760
8.7%
I 197647
8.7%
L 180463
 
7.9%
R 157180
 
6.9%
T 156821
 
6.9%
C 145508
 
6.4%
N 127290
 
5.6%
U 88486
 
3.9%
Other values (27) 473130
20.8%
Common
ValueCountFrequency (%)
270035
75.2%
. 22832
 
6.4%
1 10249
 
2.9%
2 8018
 
2.2%
0 6255
 
1.7%
3 5650
 
1.6%
4 4758
 
1.3%
, 4436
 
1.2%
8 4332
 
1.2%
6 4263
 
1.2%
Other values (22) 18319
 
5.1%
Unknown
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2629463
99.7%
None 7131
 
0.3%
PUA 9
 
< 0.1%
Punctuation 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 290573
11.1%
270035
10.3%
E 262597
10.0%
O 197760
 
7.5%
I 197647
 
7.5%
L 180463
 
6.9%
R 157180
 
6.0%
T 156821
 
6.0%
C 145508
 
5.5%
N 127290
 
4.8%
Other values (40) 643589
24.5%
None
ValueCountFrequency (%)
Ú 2709
38.0%
Ó 1276
17.9%
Ñ 1076
 
15.1%
É 895
 
12.6%
Á 692
 
9.7%
Í 373
 
5.2%
Ü 53
 
0.7%
¿ 21
 
0.3%
à 13
 
0.2%
ż 7
 
0.1%
Other values (6) 16
 
0.2%
PUA
ValueCountFrequency (%)
9
100.0%
Punctuation
ValueCountFrequency (%)
“ 5
62.5%
‰ 2
 
25.0%
‘ 1
 
12.5%

CV_CCT
Text

Distinct17316
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:18.814567image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters736630
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique303 ?
Unique (%)0.4%

Sample

1st row01DBH0004I
2nd row01DBH0004I
3rd row01DBH0004I
4th row01DBH0004I
5th row01DBH0005H
ValueCountFrequency (%)
15pbh3443i 24
 
< 0.1%
28pbh0405p 20
 
< 0.1%
02pbh0130j 18
 
< 0.1%
02pbh0132h 18
 
< 0.1%
25ubh0008e 16
 
< 0.1%
28pbh0013b 16
 
< 0.1%
28pbh0226d 13
 
< 0.1%
28pbh0214z 13
 
< 0.1%
28pbh0248p 13
 
< 0.1%
25ubh0011s 12
 
< 0.1%
Other values (17306) 73500
99.8%
2024-03-09T21:10:19.384480image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 148921
20.2%
1 75256
 
10.2%
2 52679
 
7.2%
B 48495
 
6.6%
H 46592
 
6.3%
E 44478
 
6.0%
3 37636
 
5.1%
P 28761
 
3.9%
5 26634
 
3.6%
4 24178
 
3.3%
Other values (26) 203000
27.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 441978
60.0%
Uppercase Letter 294652
40.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
B 48495
16.5%
H 46592
15.8%
E 44478
15.1%
P 28761
9.8%
T 24132
8.2%
K 16125
 
5.5%
C 11289
 
3.8%
S 9204
 
3.1%
M 7802
 
2.6%
U 6428
 
2.2%
Other values (16) 51346
17.4%
Decimal Number
ValueCountFrequency (%)
0 148921
33.7%
1 75256
17.0%
2 52679
 
11.9%
3 37636
 
8.5%
5 26634
 
6.0%
4 24178
 
5.5%
6 20285
 
4.6%
7 19735
 
4.5%
8 19116
 
4.3%
9 17538
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 441978
60.0%
Latin 294652
40.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
B 48495
16.5%
H 46592
15.8%
E 44478
15.1%
P 28761
9.8%
T 24132
8.2%
K 16125
 
5.5%
C 11289
 
3.8%
S 9204
 
3.1%
M 7802
 
2.6%
U 6428
 
2.2%
Other values (16) 51346
17.4%
Common
ValueCountFrequency (%)
0 148921
33.7%
1 75256
17.0%
2 52679
 
11.9%
3 37636
 
8.5%
5 26634
 
6.0%
4 24178
 
5.5%
6 20285
 
4.6%
7 19735
 
4.5%
8 19116
 
4.3%
9 17538
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 736630
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 148921
20.2%
1 75256
 
10.2%
2 52679
 
7.2%
B 48495
 
6.6%
H 46592
 
6.3%
E 44478
 
6.0%
3 37636
 
5.1%
P 28761
 
3.9%
5 26634
 
3.6%
4 24178
 
3.3%
Other values (26) 203000
27.6%

CV_TURNO
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.6 KiB
1.0
45132 
2.0
21257 
4.0
6183 
3.0
 
1067
5.0
 
24

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 45132
61.3%
2.0 21257
28.9%
4.0 6183
 
8.4%
3.0 1067
 
1.4%
5.0 24
 
< 0.1%

Common Values (Plot)

2024-03-09T21:10:19.639430image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

C_TURNO
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.6 KiB
MATUTINO
45132 
VESPERTINO
21257 
DISCONTINUO
6183 
NOCTURNO
 
1067
CONTINUO
 
24

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMATUTINO
2nd rowMATUTINO
3rd rowMATUTINO
4th rowMATUTINO
5th rowMATUTINO

Common Values

ValueCountFrequency (%)
MATUTINO 45132
61.3%
VESPERTINO 21257
28.9%
DISCONTINUO 6183
 
8.4%
NOCTURNO 1067
 
1.4%
CONTINUO 24
 
< 0.1%

Common Values (Plot)

2024-03-09T21:10:19.859269image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

NOMBRECT
Text

Distinct17905
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:20.216272image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length115
Median length91
Mean length35.98248782
Min length4

Characters and Unicode

Total characters2650578
Distinct characters74
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3318 ?
Unique (%)4.5%

Sample

1st rowCENTRO DE ESTUDIOS DE BACHILLERATO 8/4 FRIDA KAHLO
2nd rowCENTRO DE ESTUDIOS DE BACHILLERATO 8/4 FRIDA KAHLO
3rd rowCENTRO DE ESTUDIOS DE BACHILLERATO 8/4 FRIDA KAHLO
4th rowCENTRO DE ESTUDIOS DE BACHILLERATO 8/4 FRIDA KAHLO
5th rowCENTRO DE ESTUDIOS DE BACHILLERATO 8/5 EZEQUIEL A. CHAVEZ
ValueCountFrequency (%)
de 27752
 
8.0%
telebachillerato 18853
 
5.5%
comunitario 13155
 
3.8%
num 10565
 
3.1%
preparatoria 10222
 
3.0%
colegio 9213
 
2.7%
centro 7788
 
2.3%
plantel 5925
 
1.7%
instituto 5920
 
1.7%
escuela 5626
 
1.6%
Other values (8668) 230127
66.7%
2024-03-09T21:10:20.917242image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 292312
11.0%
271945
10.3%
E 264163
10.0%
O 198711
 
7.5%
I 198590
 
7.5%
L 181066
 
6.8%
R 158230
 
6.0%
T 157559
 
5.9%
C 146001
 
5.5%
N 127855
 
4.8%
Other values (64) 654146
24.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 2290166
86.4%
Space Separator 271945
 
10.3%
Decimal Number 54328
 
2.0%
Other Punctuation 30662
 
1.2%
Open Punctuation 1278
 
< 0.1%
Close Punctuation 1264
 
< 0.1%
Dash Punctuation 871
 
< 0.1%
Currency Symbol 22
 
< 0.1%
Private Use 19
 
< 0.1%
Control 8
 
< 0.1%
Other values (4) 15
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 292312
12.8%
E 264163
11.5%
O 198711
8.7%
I 198590
8.7%
L 181066
 
7.9%
R 158230
 
6.9%
T 157559
 
6.9%
C 146001
 
6.4%
N 127855
 
5.6%
U 88738
 
3.9%
Other values (25) 476941
20.8%
Decimal Number
ValueCountFrequency (%)
1 10252
18.9%
2 8013
14.7%
0 6288
11.6%
3 5651
10.4%
4 4768
8.8%
8 4347
8.0%
6 4257
7.8%
5 4078
 
7.5%
7 3403
 
6.3%
9 3271
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 22736
74.2%
, 4572
 
14.9%
" 2976
 
9.7%
/ 225
 
0.7%
? 84
 
0.3%
' 51
 
0.2%
¿ 12
 
< 0.1%
@ 4
 
< 0.1%
‰ 2
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
ż 4
57.1%
ş 1
 
14.3%
š 1
 
14.3%
s 1
 
14.3%
Private Use
ValueCountFrequency (%)
7
36.8%
7
36.8%
5
26.3%
Control
ValueCountFrequency (%)
“ 5
62.5%
‰ 2
 
25.0%
š 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 1276
99.8%
[ 2
 
0.2%
Currency Symbol
ValueCountFrequency (%)
¥ 20
90.9%
¤ 2
 
9.1%
Space Separator
ValueCountFrequency (%)
271945
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1264
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 871
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 4
100.0%
Other Letter
ValueCountFrequency (%)
º 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
¨ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2290176
86.4%
Common 360383
 
13.6%
Unknown 19
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 292312
12.8%
E 264163
11.5%
O 198711
8.7%
I 198590
8.7%
L 181066
 
7.9%
R 158230
 
6.9%
T 157559
 
6.9%
C 146001
 
6.4%
N 127855
 
5.6%
U 88738
 
3.9%
Other values (30) 476951
20.8%
Common
ValueCountFrequency (%)
271945
75.5%
. 22736
 
6.3%
1 10252
 
2.8%
2 8013
 
2.2%
0 6288
 
1.7%
3 5651
 
1.6%
4 4768
 
1.3%
, 4572
 
1.3%
8 4347
 
1.2%
6 4257
 
1.2%
Other values (21) 17554
 
4.9%
Unknown
ValueCountFrequency (%)
7
36.8%
7
36.8%
5
26.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2642762
99.7%
None 7791
 
0.3%
PUA 19
 
< 0.1%
Punctuation 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 292312
11.1%
271945
10.3%
E 264163
10.0%
O 198711
 
7.5%
I 198590
 
7.5%
L 181066
 
6.9%
R 158230
 
6.0%
T 157559
 
6.0%
C 146001
 
5.5%
N 127855
 
4.8%
Other values (39) 646330
24.5%
None
ValueCountFrequency (%)
Ú 2781
35.7%
Ó 1395
17.9%
Ñ 1212
15.6%
É 1051
 
13.5%
Á 764
 
9.8%
Í 465
 
6.0%
Ü 55
 
0.7%
¥ 20
 
0.3%
¿ 12
 
0.2%
à 11
 
0.1%
Other values (10) 25
 
0.3%
PUA
ValueCountFrequency (%)
7
36.8%
7
36.8%
5
26.3%
Punctuation
ValueCountFrequency (%)
“ 4
66.7%
‰ 2
33.3%

CV_ENT_ADMNISTRATIVA
Categorical

Distinct32
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size648.7 KiB
30.0
7031 
15.0
6839 
21.0
6755 
14.0
 
4299
11.0
 
4267
Other values (27)
44472 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
30.0 7031
 
9.5%
15.0 6839
 
9.3%
21.0 6755
 
9.2%
14.0 4299
 
5.8%
11.0 4267
 
5.8%
7.0 3767
 
5.1%
12.0 3182
 
4.3%
16.0 3080
 
4.2%
20.0 2854
 
3.9%
5.0 2323
 
3.2%
Other values (22) 29266
39.7%

ENT_ADMINISTRATIVA
Categorical

Distinct32
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size648.7 KiB
VERACRUZ DE IGNACIO DE LA LLAVE
7031 
MÉXICO
6839 
PUEBLA
6755 
JALISCO
 
4299
GUANAJUATO
 
4267
Other values (27)
44472 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAGUASCALIENTES
2nd rowAGUASCALIENTES
3rd rowAGUASCALIENTES
4th rowAGUASCALIENTES
5th rowAGUASCALIENTES

Common Values

ValueCountFrequency (%)
VERACRUZ DE IGNACIO DE LA LLAVE 7031
 
9.5%
MÉXICO 6839
 
9.3%
PUEBLA 6755
 
9.2%
JALISCO 4299
 
5.8%
GUANAJUATO 4267
 
5.8%
CHIAPAS 3767
 
5.1%
GUERRERO 3182
 
4.3%
MICHOACÁN DE OCAMPO 3080
 
4.2%
OAXACA 2854
 
3.9%
COAHUILA DE ZARAGOZA 2323
 
3.2%
Other values (22) 29266
39.7%

CV_ENT_INMUEBLE
Categorical

Distinct32
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size648.7 KiB
30.0
7031 
15.0
6839 
21.0
6755 
14.0
 
4299
11.0
 
4267
Other values (27)
44472 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
30.0 7031
 
9.5%
15.0 6839
 
9.3%
21.0 6755
 
9.2%
14.0 4299
 
5.8%
11.0 4267
 
5.8%
7.0 3767
 
5.1%
12.0 3182
 
4.3%
16.0 3080
 
4.2%
20.0 2854
 
3.9%
5.0 2323
 
3.2%
Other values (22) 29266
39.7%

ENTIDAD_INMUEBLE
Categorical

Distinct32
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size648.7 KiB
VERACRUZ DE IGNACIO DE LA LLAVE
7031 
MÉXICO
6839 
PUEBLA
6755 
JALISCO
 
4299
GUANAJUATO
 
4267
Other values (27)
44472 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAGUASCALIENTES
2nd rowAGUASCALIENTES
3rd rowAGUASCALIENTES
4th rowAGUASCALIENTES
5th rowAGUASCALIENTES

Common Values

ValueCountFrequency (%)
VERACRUZ DE IGNACIO DE LA LLAVE 7031
 
9.5%
MÉXICO 6839
 
9.3%
PUEBLA 6755
 
9.2%
JALISCO 4299
 
5.8%
GUANAJUATO 4267
 
5.8%
CHIAPAS 3767
 
5.1%
GUERRERO 3182
 
4.3%
MICHOACÁN DE OCAMPO 3080
 
4.2%
OAXACA 2854
 
3.9%
COAHUILA DE ZARAGOZA 2323
 
3.2%
Other values (22) 29266
39.7%

CV_MUN
Categorical

HIGH CARDINALITY 

Distinct436
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size738.9 KiB
39.0
 
2128
1.0
 
2034
4.0
 
1968
2.0
 
1769
5.0
 
1617
Other values (431)
64147 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
39.0 2128
 
2.9%
1.0 2034
 
2.8%
4.0 1968
 
2.7%
2.0 1769
 
2.4%
5.0 1617
 
2.2%
7.0 1616
 
2.2%
3.0 1605
 
2.2%
17.0 1599
 
2.2%
6.0 1570
 
2.1%
114.0 1494
 
2.0%
Other values (426) 56263
76.4%

C_NOM_MUN
Categorical

HIGH CARDINALITY 

Distinct2049
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size799.9 KiB
PUEBLA
 
1354
GUADALAJARA
 
1051
LEÓN
 
888
TIJUANA
 
693
ZAPOPAN
 
612
Other values (2044)
69065 

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowAGUASCALIENTES
2nd rowAGUASCALIENTES
3rd rowAGUASCALIENTES
4th rowAGUASCALIENTES
5th rowAGUASCALIENTES

Common Values

ValueCountFrequency (%)
PUEBLA 1354
 
1.8%
GUADALAJARA 1051
 
1.4%
LEÓN 888
 
1.2%
TIJUANA 693
 
0.9%
ZAPOPAN 612
 
0.8%
MORELIA 598
 
0.8%
AGUASCALIENTES 597
 
0.8%
TORREÓN 587
 
0.8%
CULIACÁN 567
 
0.8%
JUÁREZ 553
 
0.8%
Other values (2039) 66163
89.8%

CV_LOC
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct640
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size740.5 KiB
1.0
41900 
2.0
 
993
3.0
 
838
5.0
 
823
4.0
 
814
Other values (635)
28295 

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 41900
56.9%
2.0 993
 
1.3%
3.0 838
 
1.1%
5.0 823
 
1.1%
4.0 814
 
1.1%
8.0 736
 
1.0%
6.0 703
 
1.0%
9.0 635
 
0.9%
11.0 600
 
0.8%
7.0 581
 
0.8%
Other values (630) 25040
34.0%

C_NOM_LOC
Text

Distinct8043
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:21.240683image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length76
Median length48
Mean length14.41810678
Min length3

Characters and Unicode

Total characters1062081
Distinct characters53
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)0.1%

Sample

1st rowAGUASCALIENTES
2nd rowAGUASCALIENTES
3rd rowAGUASCALIENTES
4th rowAGUASCALIENTES
5th rowAGUASCALIENTES
ValueCountFrequency (%)
de 14794
 
9.2%
san 8501
 
5.3%
el 3927
 
2.4%
la 3822
 
2.4%
los 2365
 
1.5%
ciudad 2332
 
1.4%
santa 1961
 
1.2%
del 1952
 
1.2%
juárez 1943
 
1.2%
heroica 1908
 
1.2%
Other values (6260) 117962
73.1%
2024-03-09T21:10:21.906685image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 159774
15.0%
87804
 
8.3%
E 84304
 
7.9%
O 76323
 
7.2%
L 71602
 
6.7%
N 60248
 
5.7%
C 55203
 
5.2%
I 53491
 
5.0%
R 52901
 
5.0%
T 48657
 
4.6%
Other values (43) 311774
29.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 964637
90.8%
Space Separator 87818
 
8.3%
Open Punctuation 3763
 
0.4%
Close Punctuation 3763
 
0.4%
Other Punctuation 841
 
0.1%
Decimal Number 691
 
0.1%
Dash Punctuation 568
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 159774
16.6%
E 84304
 
8.7%
O 76323
 
7.9%
L 71602
 
7.4%
N 60248
 
6.2%
C 55203
 
5.7%
I 53491
 
5.5%
R 52901
 
5.5%
T 48657
 
5.0%
S 44182
 
4.6%
Other values (23) 257952
26.7%
Decimal Number
ValueCountFrequency (%)
1 234
33.9%
2 188
27.2%
3 82
 
11.9%
0 72
 
10.4%
4 32
 
4.6%
6 28
 
4.1%
8 23
 
3.3%
5 16
 
2.3%
9 8
 
1.2%
7 8
 
1.2%
Other Punctuation
ValueCountFrequency (%)
. 823
97.9%
, 9
 
1.1%
' 9
 
1.1%
Space Separator
ValueCountFrequency (%)
87804
> 99.9%
  14
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3653
97.1%
[ 110
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 3653
97.1%
] 110
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 568
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 964637
90.8%
Common 97444
 
9.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 159774
16.6%
E 84304
 
8.7%
O 76323
 
7.9%
L 71602
 
7.4%
N 60248
 
6.2%
C 55203
 
5.7%
I 53491
 
5.5%
R 52901
 
5.5%
T 48657
 
5.0%
S 44182
 
4.6%
Other values (23) 257952
26.7%
Common
ValueCountFrequency (%)
87804
90.1%
( 3653
 
3.7%
) 3653
 
3.7%
. 823
 
0.8%
- 568
 
0.6%
1 234
 
0.2%
2 188
 
0.2%
[ 110
 
0.1%
] 110
 
0.1%
3 82
 
0.1%
Other values (10) 219
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1034933
97.4%
None 27148
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 159774
15.4%
87804
 
8.5%
E 84304
 
8.1%
O 76323
 
7.4%
L 71602
 
6.9%
N 60248
 
5.8%
C 55203
 
5.3%
I 53491
 
5.2%
R 52901
 
5.1%
T 48657
 
4.7%
Other values (35) 284626
27.5%
None
ValueCountFrequency (%)
Á 10251
37.8%
Ó 5935
21.9%
Í 5193
19.1%
É 3797
 
14.0%
Ú 969
 
3.6%
Ñ 949
 
3.5%
Ü 40
 
0.1%
  14
 
0.1%

C_NOM_VIALIDAD
Text

Distinct10016
Distinct (%)13.6%
Missing6
Missing (%)< 0.1%
Memory size1.1 MiB
2024-03-09T21:10:22.241642image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length183
Median length132
Mean length22.27694584
Min length1

Characters and Unicode

Total characters1640853
Distinct characters97
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1153 ?
Unique (%)1.6%

Sample

1st rowAVENIDA PROFESOR JOSE TRINIDAD VELA SALAS
2nd rowAVENIDA PROFESOR JOSE TRINIDAD VELA SALAS
3rd rowAVENIDA PROFESOR JOSE TRINIDAD VELA SALAS
4th rowAVENIDA PROFESOR JOSE TRINIDAD VELA SALAS
5th rowAVENIDA PROFESOR JOSE TRINIDAD VELA SALAS
ValueCountFrequency (%)
calle 46056
 
18.8%
ninguno 20079
 
8.2%
avenida 10103
 
4.1%
de 8902
 
3.6%
carretera 4664
 
1.9%
conocido 3492
 
1.4%
la 2730
 
1.1%
kilometro 2460
 
1.0%
a 2163
 
0.9%
san 1934
 
0.8%
Other values (6105) 142007
58.1%
2024-03-09T21:10:22.907171image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 201610
12.3%
175094
10.7%
E 160310
9.8%
L 154290
9.4%
N 134607
 
8.2%
O 120555
 
7.3%
I 103700
 
6.3%
C 102979
 
6.3%
R 87013
 
5.3%
D 51453
 
3.1%
Other values (87) 349242
21.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1433600
87.4%
Space Separator 175096
 
10.7%
Decimal Number 22774
 
1.4%
Dash Punctuation 3313
 
0.2%
Other Punctuation 3295
 
0.2%
Math Symbol 963
 
0.1%
Lowercase Letter 677
 
< 0.1%
Open Punctuation 569
 
< 0.1%
Close Punctuation 545
 
< 0.1%
Currency Symbol 6
 
< 0.1%
Other values (4) 15
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 201610
14.1%
E 160310
11.2%
L 154290
10.8%
N 134607
9.4%
O 120555
8.4%
I 103700
 
7.2%
C 102979
 
7.2%
R 87013
 
6.1%
D 51453
 
3.6%
U 50139
 
3.5%
Other values (26) 266944
18.6%
Lowercase Letter
ValueCountFrequency (%)
a 95
14.0%
e 90
13.3%
r 70
10.3%
o 60
8.9%
i 46
 
6.8%
t 42
 
6.2%
l 38
 
5.6%
n 36
 
5.3%
s 33
 
4.9%
d 32
 
4.7%
Other values (15) 135
19.9%
Decimal Number
ValueCountFrequency (%)
1 5005
22.0%
0 3792
16.7%
5 3246
14.3%
2 3104
13.6%
3 1872
 
8.2%
6 1542
 
6.8%
4 1387
 
6.1%
7 1003
 
4.4%
8 945
 
4.1%
9 878
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 2977
90.3%
, 146
 
4.4%
/ 90
 
2.7%
? 65
 
2.0%
; 8
 
0.2%
" 6
 
0.2%
' 3
 
0.1%
Private Use
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%
Space Separator
ValueCountFrequency (%)
175094
> 99.9%
  2
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 3312
> 99.9%
– 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 962
99.9%
| 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 565
99.3%
[ 4
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 541
99.3%
} 4
 
0.7%
Other Symbol
ValueCountFrequency (%)
° 4
66.7%
¦ 2
33.3%
Control
ValueCountFrequency (%)
š 2
66.7%
– 1
33.3%
Currency Symbol
ValueCountFrequency (%)
¥ 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
¨ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1434277
87.4%
Common 206571
 
12.6%
Unknown 5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 201610
14.1%
E 160310
11.2%
L 154290
10.8%
N 134607
9.4%
O 120555
8.4%
I 103700
 
7.2%
C 102979
 
7.2%
R 87013
 
6.1%
D 51453
 
3.6%
U 50139
 
3.5%
Other values (51) 267621
18.7%
Common
ValueCountFrequency (%)
175094
84.8%
1 5005
 
2.4%
0 3792
 
1.8%
- 3312
 
1.6%
5 3246
 
1.6%
2 3104
 
1.5%
. 2977
 
1.4%
3 1872
 
0.9%
6 1542
 
0.7%
4 1387
 
0.7%
Other values (23) 5240
 
2.5%
Unknown
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1633316
99.5%
None 7531
 
0.5%
PUA 5
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 201610
12.3%
175094
10.7%
E 160310
9.8%
L 154290
9.4%
N 134607
 
8.2%
O 120555
 
7.4%
I 103700
 
6.3%
C 102979
 
6.3%
R 87013
 
5.3%
D 51453
 
3.2%
Other values (63) 341705
20.9%
None
ValueCountFrequency (%)
Ó 3087
41.0%
Á 1299
17.2%
Í 1093
 
14.5%
É 1024
 
13.6%
Ñ 882
 
11.7%
Ú 103
 
1.4%
ó 10
 
0.1%
¥ 6
 
0.1%
Ë 4
 
0.1%
à 4
 
0.1%
Other values (10) 19
 
0.3%
PUA
ValueCountFrequency (%)
2
40.0%
2
40.0%
1
20.0%
Punctuation
ValueCountFrequency (%)
– 1
100.0%

N_EXTNUM
Real number (ℝ)

ZEROS 

Distinct1606
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean322.4924182
Minimum0
Maximum34900
Zeros45891
Zeros (%)62.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:23.158852image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3100
95-th percentile1504
Maximum34900
Range34900
Interquartile range (IQR)100

Descriptive statistics

Standard deviation1426.881611
Coefficient of variation (CV)4.424543123
Kurtosis165.255006
Mean322.4924182
Median Absolute Deviation (MAD)0
Skewness10.8594149
Sum23755759
Variance2035991.132
MonotonicityNot monotonic
2024-03-09T21:10:23.446360image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 45891
62.3%
1 928
 
1.3%
2 488
 
0.7%
5 370
 
0.5%
100 344
 
0.5%
3 337
 
0.5%
4 291
 
0.4%
10 249
 
0.3%
12 222
 
0.3%
6 219
 
0.3%
Other values (1596) 24324
33.0%
ValueCountFrequency (%)
0 45891
62.3%
1 928
 
1.3%
2 488
 
0.7%
3 337
 
0.5%
4 291
 
0.4%
ValueCountFrequency (%)
34900 1
 
< 0.1%
33982 4
< 0.1%
33419 4
< 0.1%
33205 4
< 0.1%
31219 8
< 0.1%

CONTROL
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.5 KiB
PÚBLICO
46563 
PRIVADO
27100 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPÚBLICO
2nd rowPÚBLICO
3rd rowPÚBLICO
4th rowPÚBLICO
5th rowPÚBLICO

Common Values

ValueCountFrequency (%)
PÚBLICO 46563
63.2%
PRIVADO 27100
36.8%

Common Values (Plot)

2024-03-09T21:10:23.667796image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

SUBCONTROL
Categorical

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.6 KiB
ESTATAL
40647 
PRIVADO
25677 
AUTÓNOMO
 
3973
FEDERAL
 
1942
SUBSIDIO
 
1423

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowFEDERAL
2nd rowFEDERAL
3rd rowFEDERAL
4th rowFEDERAL
5th rowFEDERAL

Common Values

ValueCountFrequency (%)
ESTATAL 40647
55.2%
PRIVADO 25677
34.9%
AUTÓNOMO 3973
 
5.4%
FEDERAL 1942
 
2.6%
SUBSIDIO 1423
 
1.9%
FEDERAL TRANSFERIDO 1
 
< 0.1%

Common Values (Plot)

2024-03-09T21:10:23.872396image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

TIPO
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.5 KiB
MEDIA SUPERIOR
73663 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMEDIA SUPERIOR
2nd rowMEDIA SUPERIOR
3rd rowMEDIA SUPERIOR
4th rowMEDIA SUPERIOR
5th rowMEDIA SUPERIOR

Common Values

ValueCountFrequency (%)
MEDIA SUPERIOR 73663
100.0%

Common Values (Plot)

2024-03-09T21:10:24.079496image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

NIVEL
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.5 KiB
MEDIA SUPERIOR
73663 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMEDIA SUPERIOR
2nd rowMEDIA SUPERIOR
3rd rowMEDIA SUPERIOR
4th rowMEDIA SUPERIOR
5th rowMEDIA SUPERIOR

Common Values

ValueCountFrequency (%)
MEDIA SUPERIOR 73663
100.0%

Common Values (Plot)

2024-03-09T21:10:24.239863image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

SUBNIVEL
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.5 KiB
BACHILLERATO GENERAL
73663 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBACHILLERATO GENERAL
2nd rowBACHILLERATO GENERAL
3rd rowBACHILLERATO GENERAL
4th rowBACHILLERATO GENERAL
5th rowBACHILLERATO GENERAL

Common Values

ValueCountFrequency (%)
BACHILLERATO GENERAL 73663
100.0%

Common Values (Plot)

2024-03-09T21:10:24.389037image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

CV_CARACTERIZAN1
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.5 KiB
0.0
43365 
1.0
30298 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 43365
58.9%
1.0 30298
41.1%

Common Values (Plot)

2024-03-09T21:10:24.560673image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

C_CARACTERIZAN1
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.5 KiB
NO APLICA
43365 
SERVICIOS
30298 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNO APLICA
2nd rowNO APLICA
3rd rowNO APLICA
4th rowNO APLICA
5th rowNO APLICA

Common Values

ValueCountFrequency (%)
NO APLICA 43365
58.9%
SERVICIOS 30298
41.1%

Common Values (Plot)

2024-03-09T21:10:24.749343image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

CV_CARACTERIZAN2
Categorical

IMBALANCE 

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size648.1 KiB
0.0
43365 
35.0
13325 
34.0
8104 
31.0
5001 
30.0
 
1282
Other values (11)
 
2586

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 43365
58.9%
35.0 13325
 
18.1%
34.0 8104
 
11.0%
31.0 5001
 
6.8%
30.0 1282
 
1.7%
36.0 1143
 
1.6%
28.0 511
 
0.7%
10.0 415
 
0.6%
29.0 221
 
0.3%
32.0 192
 
0.3%
Other values (6) 104
 
0.1%

C_CARACTERIZAN2
Categorical

IMBALANCE 

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size648.1 KiB
NO APLICA
43365 
TELEBACHILLERATO COMUNITARIO
13325 
TELEBACHILLERATO
8104 
BACHILLERATO A DISTANCIA
5001 
BACHILLERATO POR COOPERACIÓN
 
1282
Other values (11)
 
2586

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNO APLICA
2nd rowNO APLICA
3rd rowNO APLICA
4th rowNO APLICA
5th rowNO APLICA

Common Values

ValueCountFrequency (%)
NO APLICA 43365
58.9%
TELEBACHILLERATO COMUNITARIO 13325
 
18.1%
TELEBACHILLERATO 8104
 
11.0%
BACHILLERATO A DISTANCIA 5001
 
6.8%
BACHILLERATO POR COOPERACIÓN 1282
 
1.7%
CAED 1143
 
1.6%
DECRETO PRESIDENCIAL 511
 
0.7%
EXTENSION 415
 
0.6%
BACHILLERATO PEDAGÓGICO 221
 
0.3%
BACHILLERATO INTEGRAL COMUNITARIO 192
 
0.3%
Other values (6) 104
 
0.1%

CV_MODALIDAD
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.6 KiB
1.0
66560 
2.0
 
4936
3.0
 
2167

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 66560
90.4%
2.0 4936
 
6.7%
3.0 2167
 
2.9%

Common Values (Plot)

2024-03-09T21:10:24.938010image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

C_MODALIDAD
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.6 KiB
ESCOLARIZADA
66560 
MIXTA
 
4936
NO ESCOLARIZADA
 
2167

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowESCOLARIZADA
2nd rowESCOLARIZADA
3rd rowESCOLARIZADA
4th rowESCOLARIZADA
5th rowESCOLARIZADA

Common Values

ValueCountFrequency (%)
ESCOLARIZADA 66560
90.4%
MIXTA 4936
 
6.7%
NO ESCOLARIZADA 2167
 
2.9%

Common Values (Plot)

2024-03-09T21:10:25.699980image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

CV_OPCION_EDUCATIVA
Categorical

IMBALANCE 

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.8 KiB
1.0
65468 
3.0
 
4618
6.0
 
1535
2.0
 
1092
5.0
 
610
Other values (3)
 
340

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 65468
88.9%
3.0 4618
 
6.3%
6.0 1535
 
2.1%
2.0 1092
 
1.5%
5.0 610
 
0.8%
4.0 318
 
0.4%
8.0 18
 
< 0.1%
9.0 4
 
< 0.1%

Common Values (Plot)

2024-03-09T21:10:25.919873image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

C_OPCION_EDUCATIVA
Categorical

IMBALANCE 

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.8 KiB
PRESENCIAL
65468 
MIXTA
 
4618
CERTIFICACIÓN POR EVALUACIÓNES PARCIALES
 
1148
INTENSIVA
 
1092
VIRTUAL
 
610
Other values (5)
 
727

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPRESENCIAL
2nd rowPRESENCIAL
3rd rowPRESENCIAL
4th rowPRESENCIAL
5th rowPRESENCIAL

Common Values

ValueCountFrequency (%)
PRESENCIAL 65468
88.9%
MIXTA 4618
 
6.3%
CERTIFICACIÓN POR EVALUACIÓNES PARCIALES 1148
 
1.6%
INTENSIVA 1092
 
1.5%
VIRTUAL 610
 
0.8%
CERTIFICACIÓN POR EVALUACIONES PARCIALES 387
 
0.5%
AUTOPLANEADA 318
 
0.4%
EXAMEN ÚNICO 18
 
< 0.1%
EN LINEA O VIRTUAL 2
 
< 0.1%
EN LÍNEA O VIRTUAL 2
 
< 0.1%

Common Values (Plot)

2024-03-09T21:10:26.188982image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

CV_PLAN_ESTUDIO
Categorical

IMBALANCE 

Distinct47
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size648.8 KiB
0.0
68643 
2014.0
 
1113
2009.0
 
750
2017.0
 
749
2016.0
 
445
Other values (42)
 
1963

Unique

Unique7 ?
Unique (%)< 0.1%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 68643
93.2%
2014.0 1113
 
1.5%
2009.0 750
 
1.0%
2017.0 749
 
1.0%
2016.0 445
 
0.6%
2013.0 399
 
0.5%
2015.0 358
 
0.5%
2010.0 273
 
0.4%
2008.0 155
 
0.2%
2011.0 134
 
0.2%
Other values (37) 644
 
0.9%

DURACION
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean826.9741661
Minimum2
Maximum999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:26.455532image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q1999
median999
Q3999
95-th percentile999
Maximum999
Range997
Interquartile range (IQR)0

Descriptive statistics

Standard deviation376.2402295
Coefficient of variation (CV)0.454960076
Kurtosis0.9926734157
Mean826.9741661
Median Absolute Deviation (MAD)0
Skewness-1.729918893
Sum60917398
Variance141556.7103
MonotonicityNot monotonic
2024-03-09T21:10:26.639726image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
999 60926
82.7%
3 8032
 
10.9%
6 4470
 
6.1%
2 180
 
0.2%
22 44
 
0.1%
4 4
 
< 0.1%
10 4
 
< 0.1%
8 3
 
< 0.1%
ValueCountFrequency (%)
2 180
 
0.2%
3 8032
10.9%
4 4
 
< 0.1%
6 4470
6.1%
8 3
 
< 0.1%
ValueCountFrequency (%)
999 60926
82.7%
22 44
 
0.1%
10 4
 
< 0.1%
8 3
 
< 0.1%
6 4470
 
6.1%

CV_DURACION
Categorical

IMBALANCE 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.8 KiB
999.0
61032 
1.0
8102 
2.0
 
4364
5.0
 
109
12.0
 
47
Other values (2)
 
9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row999.0
2nd row999.0
3rd row999.0
4th row999.0
5th row999.0

Common Values

ValueCountFrequency (%)
999.0 61032
82.9%
1.0 8102
 
11.0%
2.0 4364
 
5.9%
5.0 109
 
0.1%
12.0 47
 
0.1%
3.0 5
 
< 0.1%
4.0 4
 
< 0.1%

Common Values (Plot)

2024-03-09T21:10:26.875390image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

C_DURACION
Categorical

IMBALANCE 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.8 KiB
NO APLICA
61032 
AÑOS
8102 
SEMESTRES
 
4364
CUATRIMESTRES
 
109
MODULAR
 
47
Other values (2)
 
9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNO APLICA
2nd rowNO APLICA
3rd rowNO APLICA
4th rowNO APLICA
5th rowNO APLICA

Common Values

ValueCountFrequency (%)
NO APLICA 61032
82.9%
AÑOS 8102
 
11.0%
SEMESTRES 4364
 
5.9%
CUATRIMESTRES 109
 
0.1%
MODULAR 47
 
0.1%
TRIMESTRES 5
 
< 0.1%
BIMESTRES 4
 
< 0.1%

Common Values (Plot)

2024-03-09T21:10:27.110817image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

CV_ESTATUS
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.6 KiB
1.0
70622 
2.0
 
2302
3.0
 
581
4.0
 
158

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 70622
95.9%
2.0 2302
 
3.1%
3.0 581
 
0.8%
4.0 158
 
0.2%

Common Values (Plot)

2024-03-09T21:10:27.339098image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

C_CARRERA_ESTATUS
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.6 KiB
Activa
70622 
Latencia
 
2302
Liquidacion
 
581
Suspendido
 
158

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowActiva
2nd rowActiva
3rd rowActiva
4th rowActiva
5th rowActiva

Common Values

ValueCountFrequency (%)
Activa 70622
95.9%
Latencia 2302
 
3.1%
Liquidacion 581
 
0.8%
Suspendido 158
 
0.2%

Common Values (Plot)

2024-03-09T21:10:27.542854image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

CV_MOTIVO
Categorical

IMBALANCE 

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.8 KiB
0.0
68757 
17.0
 
2587
7.0
 
1337
15.0
 
369
5.0
 
257
Other values (5)
 
356

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 68757
93.3%
17.0 2587
 
3.5%
7.0 1337
 
1.8%
15.0 369
 
0.5%
5.0 257
 
0.3%
19.0 128
 
0.2%
6.0 116
 
0.2%
20.0 45
 
0.1%
18.0 36
 
< 0.1%
16.0 31
 
< 0.1%

Common Values (Plot)

2024-03-09T21:10:27.794339image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

C_MOTIVO
Categorical

MISSING 

Distinct9
Distinct (%)0.2%
Missing68757
Missing (%)93.3%
Memory size647.8 KiB
Falta de alumnos
2587 
Causa administrativa
1337 
La escuela está clausurada
369 
Incumplimiento del director o responsable
 
257
Compactación de turno
 
128
Other values (4)
 
228

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCausa administrativa
2nd rowLa escuela está clausurada
3rd rowLa escuela está clausurada
4th rowCausa administrativa
5th rowCausa administrativa

Common Values

ValueCountFrequency (%)
Falta de alumnos 2587
 
3.5%
Causa administrativa 1337
 
1.8%
La escuela está clausurada 369
 
0.5%
Incumplimiento del director o responsable 257
 
0.3%
Compactación de turno 128
 
0.2%
Escuelas de nueva creación 116
 
0.2%
Cambio de turno 45
 
0.1%
No corresponde la fecha de levantamiento con el inicio de cursos de la escuela 36
 
< 0.1%
Falta de personal docente 31
 
< 0.1%
(Missing) 68757
93.3%

Common Values (Plot)

2024-03-09T21:10:28.046001image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

SUBSISTEMA_1
Categorical

Distinct10
Distinct (%)< 0.1%
Missing230
Missing (%)0.3%
Memory size647.8 KiB
Particular
25458 
Descentralizados Estado
24729 
Centralizados Estado
16146 
Autónomo
3967 
Centralizados SEMS
 
1452
Other values (5)
 
1681

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCentralizados SEMS
2nd rowCentralizados SEMS
3rd rowCentralizados SEMS
4th rowCentralizados SEMS
5th rowCentralizados SEMS

Common Values

ValueCountFrequency (%)
Particular 25458
34.6%
Descentralizados Estado 24729
33.6%
Centralizados Estado 16146
21.9%
Autónomo 3967
 
5.4%
Centralizados SEMS 1452
 
2.0%
Subsidiados de las Entidades Federativas 950
 
1.3%
Subsidiados de la SEP 472
 
0.6%
Descentralizados SEP 187
 
0.3%
Desconcentrados SEP 64
 
0.1%
Centralizados otras Secretarías u Organismos Federales 8
 
< 0.1%
(Missing) 230
 
0.3%

Common Values (Plot)

2024-03-09T21:10:28.372305image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

SUBSISTEMA_2
Categorical

Distinct26
Distinct (%)< 0.1%
Missing230
Missing (%)0.3%
Memory size648.7 KiB
PARTICULAR
25458 
TELEBACHILLERATO COMUNITARIO
13319 
TELEBACHILLERATO
8112 
BACHILLERATO ESTATAL
7547 
COBACH
6347 
Other values (21)
12650 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDGB
2nd rowDGB
3rd rowDGB
4th rowDGB
5th rowDGB

Common Values

ValueCountFrequency (%)
PARTICULAR 25458
34.6%
TELEBACHILLERATO COMUNITARIO 13319
18.1%
TELEBACHILLERATO 8112
 
11.0%
BACHILLERATO ESTATAL 7547
 
10.2%
COBACH 6347
 
8.6%
EMSAD 5005
 
6.8%
UNIVERSIDADES AUTÓNOMAS ESTATALES 3872
 
5.3%
DGB 1448
 
2.0%
PREECO 950
 
1.3%
PREFECO 472
 
0.6%
Other values (16) 903
 
1.2%
(Missing) 230
 
0.3%

SUBSISTEMA_3
Categorical

Distinct33
Distinct (%)< 0.1%
Missing230
Missing (%)0.3%
Memory size648.7 KiB
Escuela Particular de Bachillerato General
25241 
Telebachillerato Comunitario
13319 
Telebachillerato Estatal
8112 
Centro de Bachillerato General del Estado
7544 
Colegio de Bachilleres Estatal
6347 
Other values (28)
12870 

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowCentro de Estudios de Bachillerato
2nd rowCentro de Estudios de Bachillerato
3rd rowCentro de Estudios de Bachillerato
4th rowCentro de Estudios de Bachillerato
5th rowCentro de Estudios de Bachillerato

Common Values

ValueCountFrequency (%)
Escuela Particular de Bachillerato General 25241
34.3%
Telebachillerato Comunitario 13319
18.1%
Telebachillerato Estatal 8112
 
11.0%
Centro de Bachillerato General del Estado 7544
 
10.2%
Colegio de Bachilleres Estatal 6347
 
8.6%
Centro de Servicios de Educación Media Superior a Distancia 4936
 
6.7%
Bachillerto General de Universidades Autónomas Estatales 3872
 
5.3%
Centro de Atención a Estudiantes con Discapacidad 1143
 
1.6%
Preparatoria Estatal por Cooperación_Bachillerato General 950
 
1.3%
Preparatoria Federal por Cooperación 472
 
0.6%
Other values (23) 1497
 
2.0%

PERIODO
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size647.6 KiB
2021
18510 
2022
18503 
2020
18468 
2019
18182 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2020
3rd row2021
4th row2022
5th row2019

Common Values

ValueCountFrequency (%)
2021 18510
25.1%
2022 18503
25.1%
2020 18468
25.1%
2019 18182
24.7%

Common Values (Plot)

2024-03-09T21:10:28.672501image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

V1
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3180837055
Minimum0
Maximum1
Zeros50232
Zeros (%)68.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:28.876706image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4657353395
Coefficient of variation (CV)1.464191128
Kurtosis-1.389730677
Mean0.3180837055
Median Absolute Deviation (MAD)0
Skewness0.7812215151
Sum23431
Variance0.2169094064
MonotonicityNot monotonic
2024-03-09T21:10:29.080940image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 50232
68.2%
1 23431
31.8%
ValueCountFrequency (%)
0 50232
68.2%
1 23431
31.8%
ValueCountFrequency (%)
1 23431
31.8%
0 50232
68.2%

V2
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5929706908
Minimum0
Maximum1
Zeros29983
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:29.253957image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4912837542
Coefficient of variation (CV)0.8285127104
Kurtosis-1.856795053
Mean0.5929706908
Median Absolute Deviation (MAD)0
Skewness-0.3784908999
Sum43680
Variance0.2413597272
MonotonicityNot monotonic
2024-03-09T21:10:29.455614image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 43680
59.3%
0 29983
40.7%
ValueCountFrequency (%)
0 29983
40.7%
1 43680
59.3%
ValueCountFrequency (%)
1 43680
59.3%
0 29983
40.7%

E3
Text

MISSING 

Distinct131
Distinct (%)0.6%
Missing50232
Missing (%)68.2%
Memory size1.1 MiB
2024-03-09T21:10:29.684626image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length80
Median length47
Mean length39.62780078
Min length7

Characters and Unicode

Total characters928519
Distinct characters60
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)0.4%

Sample

1st rowSECRETARÍA DE EDUCACIÓN DEL GOBIERNO DEL ESTADO
2nd rowSECRETARÍA DE EDUCACIÓN DEL GOBIERNO DEL ESTADO
3rd rowUNIVERSIDADES AUTÓNOMAS
4th rowUNIVERSIDADES AUTÓNOMAS
5th rowUNIVERSIDADES AUTÓNOMAS
ValueCountFrequency (%)
del 31463
24.6%
de 14819
11.6%
gobierno 13265
10.4%
estado 13265
10.4%
educación 11964
 
9.4%
secretaría 11890
 
9.3%
general 4999
 
3.9%
dirección 4908
 
3.8%
bachillerato 4348
 
3.4%
universidades 2852
 
2.2%
Other values (223) 14102
11.0%
2024-03-09T21:10:30.300750image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 139716
15.0%
104456
11.2%
D 85525
9.2%
A 83647
9.0%
C 60699
 
6.5%
I 58707
 
6.3%
R 58431
 
6.3%
O 54621
 
5.9%
L 49819
 
5.4%
N 47917
 
5.2%
Other values (50) 184981
19.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 823532
88.7%
Space Separator 104456
 
11.2%
Other Punctuation 166
 
< 0.1%
Control 119
 
< 0.1%
Initial Punctuation 105
 
< 0.1%
Close Punctuation 48
 
< 0.1%
Open Punctuation 48
 
< 0.1%
Lowercase Letter 33
 
< 0.1%
Private Use 12
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 139716
17.0%
D 85525
10.4%
A 83647
10.2%
C 60699
7.4%
I 58707
7.1%
R 58431
7.1%
O 54621
 
6.6%
L 49819
 
6.0%
N 47917
 
5.8%
S 38535
 
4.7%
Other values (21) 145915
17.7%
Lowercase Letter
ValueCountFrequency (%)
a 5
15.2%
t 5
15.2%
i 4
12.1%
r 3
9.1%
o 3
9.1%
n 3
9.1%
s 2
 
6.1%
e 2
 
6.1%
u 1
 
3.0%
m 1
 
3.0%
Other values (4) 4
12.1%
Other Punctuation
ValueCountFrequency (%)
" 124
74.7%
. 27
 
16.3%
, 9
 
5.4%
? 3
 
1.8%
‰ 3
 
1.8%
Control
ValueCountFrequency (%)
 109
91.6%
‰ 4
 
3.4%
‘ 3
 
2.5%
“ 2
 
1.7%
 1
 
0.8%
Space Separator
ValueCountFrequency (%)
104456
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Private Use
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 823565
88.7%
Common 104942
 
11.3%
Unknown 12
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 139716
17.0%
D 85525
10.4%
A 83647
10.2%
C 60699
7.4%
I 58707
7.1%
R 58431
7.1%
O 54621
 
6.6%
L 49819
 
6.0%
N 47917
 
5.8%
S 38535
 
4.7%
Other values (35) 145948
17.7%
Common
ValueCountFrequency (%)
104456
99.5%
" 124
 
0.1%
 109
 
0.1%
“ 105
 
0.1%
) 48
 
< 0.1%
( 48
 
< 0.1%
. 27
 
< 0.1%
, 9
 
< 0.1%
‰ 4
 
< 0.1%
‘ 3
 
< 0.1%
Other values (4) 9
 
< 0.1%
Unknown
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 892954
96.2%
None 35445
 
3.8%
Punctuation 108
 
< 0.1%
PUA 12
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 139716
15.6%
104456
11.7%
D 85525
9.6%
A 83647
9.4%
C 60699
6.8%
I 58707
 
6.6%
R 58431
 
6.5%
O 54621
 
6.1%
L 49819
 
5.6%
N 47917
 
5.4%
Other values (36) 149416
16.7%
None
ValueCountFrequency (%)
Ó 22062
62.2%
Í 11893
33.6%
É 918
 
2.6%
à 342
 
1.0%
 109
 
0.3%
Ú 63
 
0.2%
Á 48
 
0.1%
‰ 4
 
< 0.1%
‘ 3
 
< 0.1%
“ 2
 
< 0.1%
Punctuation
ValueCountFrequency (%)
“ 105
97.2%
‰ 3
 
2.8%
PUA
ValueCountFrequency (%)
12
100.0%

E4
Text

MISSING 

Distinct6227
Distinct (%)27.0%
Missing50627
Missing (%)68.7%
Memory size1.1 MiB
2024-03-09T21:10:30.590240image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length100
Median length40
Mean length9.640258725
Min length1

Characters and Unicode

Total characters222073
Distinct characters86
Distinct categories15 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1354 ?
Unique (%)5.9%

Sample

1st row2285
2nd row2286
3rd rowCPB-680807-UAA
4th rowCPB-680807-UAA
5th rowCPB-680807-UAA
ValueCountFrequency (%)
0 1652
 
6.6%
123 428
 
1.7%
s/n 224
 
0.9%
revoe 220
 
0.9%
no 166
 
0.7%
a-36 147
 
0.6%
n/d 139
 
0.6%
oficio 133
 
0.5%
00000 114
 
0.5%
de 72
 
0.3%
Other values (6316) 21559
86.7%
2024-03-09T21:10:31.172471image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38623
17.4%
1 26477
 
11.9%
2 21842
 
9.8%
/ 15061
 
6.8%
- 8661
 
3.9%
9 8118
 
3.7%
4 8082
 
3.6%
3 8003
 
3.6%
7 7930
 
3.6%
5 7416
 
3.3%
Other values (76) 71860
32.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 140060
63.1%
Uppercase Letter 50729
 
22.8%
Other Punctuation 18072
 
8.1%
Dash Punctuation 8661
 
3.9%
Lowercase Letter 2534
 
1.1%
Space Separator 1951
 
0.9%
Open Punctuation 14
 
< 0.1%
Close Punctuation 14
 
< 0.1%
Connector Punctuation 12
 
< 0.1%
Control 8
 
< 0.1%
Other values (5) 18
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 7405
14.6%
S 6647
13.1%
B 5759
11.4%
M 5074
10.0%
P 3115
 
6.1%
C 2947
 
5.8%
I 2600
 
5.1%
A 2513
 
5.0%
H 2203
 
4.3%
G 2196
 
4.3%
Other values (18) 10270
20.2%
Lowercase Letter
ValueCountFrequency (%)
b 358
14.1%
g 285
11.2%
o 249
9.8%
a 232
9.2%
c 223
8.8%
i 183
 
7.2%
u 164
 
6.5%
n 138
 
5.4%
m 123
 
4.9%
e 119
 
4.7%
Other values (15) 460
18.2%
Decimal Number
ValueCountFrequency (%)
0 38623
27.6%
1 26477
18.9%
2 21842
15.6%
9 8118
 
5.8%
4 8082
 
5.8%
3 8003
 
5.7%
7 7930
 
5.7%
5 7416
 
5.3%
8 7026
 
5.0%
6 6543
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/ 15061
83.3%
. 2963
 
16.4%
" 21
 
0.1%
, 10
 
0.1%
: 6
 
< 0.1%
# 6
 
< 0.1%
? 3
 
< 0.1%
¡ 1
 
< 0.1%
! 1
 
< 0.1%
Control
ValueCountFrequency (%)
“ 4
50.0%
€ 3
37.5%
š 1
 
12.5%
Currency Symbol
ValueCountFrequency (%)
€ 3
50.0%
¤ 3
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 8661
100.0%
Space Separator
ValueCountFrequency (%)
1951
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 12
100.0%
Other Symbol
ValueCountFrequency (%)
° 4
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 4
100.0%
Private Use
ValueCountFrequency (%)
2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 168808
76.0%
Latin 53263
 
24.0%
Unknown 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 7405
13.9%
S 6647
12.5%
B 5759
10.8%
M 5074
 
9.5%
P 3115
 
5.8%
C 2947
 
5.5%
I 2600
 
4.9%
A 2513
 
4.7%
H 2203
 
4.1%
G 2196
 
4.1%
Other values (43) 12804
24.0%
Common
ValueCountFrequency (%)
0 38623
22.9%
1 26477
15.7%
2 21842
12.9%
/ 15061
 
8.9%
- 8661
 
5.1%
9 8118
 
4.8%
4 8082
 
4.8%
3 8003
 
4.7%
7 7930
 
4.7%
5 7416
 
4.4%
Other values (22) 18595
11.0%
Unknown
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 222025
> 99.9%
None 39
 
< 0.1%
Punctuation 4
 
< 0.1%
Currency Symbols 3
 
< 0.1%
PUA 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38623
17.4%
1 26477
 
11.9%
2 21842
 
9.8%
/ 15061
 
6.8%
- 8661
 
3.9%
9 8118
 
3.7%
4 8082
 
3.6%
3 8003
 
3.6%
7 7930
 
3.6%
5 7416
 
3.3%
Other values (62) 71812
32.3%
None
ValueCountFrequency (%)
â 12
30.8%
° 4
 
10.3%
à 4
 
10.3%
“ 4
 
10.3%
 4
 
10.3%
€ 3
 
7.7%
¤ 3
 
7.7%
ú 2
 
5.1%
š 1
 
2.6%
š 1
 
2.6%
Punctuation
ValueCountFrequency (%)
“ 4
100.0%
Currency Symbols
ValueCountFrequency (%)
€ 3
100.0%
PUA
ValueCountFrequency (%)
2
100.0%

V5
Real number (ℝ)

ZEROS 

Distinct88
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean605.9527171
Minimum0
Maximum2058
Zeros51387
Zeros (%)69.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:31.460267image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31996
95-th percentile2017
Maximum2058
Range2058
Interquartile range (IQR)1996

Descriptive statistics

Standard deviation920.459868
Coefficient of variation (CV)1.519029195
Kurtosis-1.258128388
Mean605.9527171
Median Absolute Deviation (MAD)0
Skewness0.8610004384
Sum44636295
Variance847246.3686
MonotonicityNot monotonic
2024-03-09T21:10:31.729111image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 51387
69.8%
2017 1223
 
1.7%
2016 1172
 
1.6%
2018 1065
 
1.4%
2011 1030
 
1.4%
2013 1017
 
1.4%
2019 1011
 
1.4%
2009 932
 
1.3%
2010 906
 
1.2%
2012 833
 
1.1%
Other values (78) 13087
 
17.8%
ValueCountFrequency (%)
0 51387
69.8%
6 1
 
< 0.1%
97 1
 
< 0.1%
1882 3
 
< 0.1%
1894 1
 
< 0.1%
ValueCountFrequency (%)
2058 2
 
< 0.1%
2033 1
 
< 0.1%
2022 129
 
0.2%
2021 312
0.4%
2020 333
0.5%

V6
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.083081058
Minimum0
Maximum107
Zeros51387
Zeros (%)69.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:31.939368image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile10
Maximum107
Range107
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.599162791
Coefficient of variation (CV)1.727807363
Kurtosis10.18000035
Mean2.083081058
Median Absolute Deviation (MAD)0
Skewness1.724739227
Sum153446
Variance12.95397279
MonotonicityNot monotonic
2024-03-09T21:10:32.155613image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 51387
69.8%
8 3748
 
5.1%
9 2636
 
3.6%
7 2503
 
3.4%
6 2094
 
2.8%
5 1929
 
2.6%
10 1737
 
2.4%
1 1600
 
2.2%
11 1488
 
2.0%
3 1243
 
1.7%
Other values (4) 3298
 
4.5%
ValueCountFrequency (%)
0 51387
69.8%
1 1600
 
2.2%
2 1057
 
1.4%
3 1243
 
1.7%
4 1020
 
1.4%
ValueCountFrequency (%)
107 1
 
< 0.1%
12 1220
1.7%
11 1488
2.0%
10 1737
2.4%
9 2636
3.6%

V7
Real number (ℝ)

SKEWED  ZEROS 

Distinct34
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.608772382
Minimum0
Maximum2019
Zeros51387
Zeros (%)69.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:32.405495image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile26
Maximum2019
Range2019
Interquartile range (IQR)5

Descriptive statistics

Standard deviation11.31852167
Coefficient of variation (CV)2.455864758
Kurtosis13619.70596
Mean4.608772382
Median Absolute Deviation (MAD)0
Skewness77.2907752
Sum339496
Variance128.1089328
MonotonicityNot monotonic
2024-03-09T21:10:32.666177image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 51387
69.8%
1 1462
 
2.0%
10 1012
 
1.4%
17 950
 
1.3%
15 924
 
1.3%
5 865
 
1.2%
30 858
 
1.2%
12 777
 
1.1%
28 775
 
1.1%
11 771
 
1.0%
Other values (24) 13882
 
18.8%
ValueCountFrequency (%)
0 51387
69.8%
1 1462
 
2.0%
2 613
 
0.8%
3 627
 
0.9%
4 619
 
0.8%
ValueCountFrequency (%)
2019 1
 
< 0.1%
133 1
 
< 0.1%
31 348
0.5%
30 858
1.2%
29 625
0.8%

V8
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3968613822
Minimum0
Maximum1
Zeros44429
Zeros (%)60.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:32.885952image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.489250115
Coefficient of variation (CV)1.232798496
Kurtosis-1.822277085
Mean0.3968613822
Median Absolute Deviation (MAD)0
Skewness0.4216306342
Sum29234
Variance0.239365675
MonotonicityNot monotonic
2024-03-09T21:10:33.074688image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 44429
60.3%
1 29234
39.7%
ValueCountFrequency (%)
0 44429
60.3%
1 29234
39.7%
ValueCountFrequency (%)
1 29234
39.7%
0 44429
60.3%

V9
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5320038554
Minimum0
Maximum1
Zeros34474
Zeros (%)46.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:33.263460image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4989780889
Coefficient of variation (CV)0.9379219415
Kurtosis-1.983597821
Mean0.5320038554
Median Absolute Deviation (MAD)0
Skewness-0.1282810811
Sum39189
Variance0.2489791332
MonotonicityNot monotonic
2024-03-09T21:10:33.442608image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 39189
53.2%
0 34474
46.8%
ValueCountFrequency (%)
0 34474
46.8%
1 39189
53.2%
ValueCountFrequency (%)
1 39189
53.2%
0 34474
46.8%

V10
Real number (ℝ)

ZEROS 

Distinct70
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1871.543869
Minimum0
Maximum2022
Zeros5261
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:33.692919image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12012
median2018
Q32018
95-th percentile2019
Maximum2022
Range2022
Interquartile range (IQR)6

Descriptive statistics

Standard deviation519.0704444
Coefficient of variation (CV)0.2773487991
Kurtosis9.076741674
Mean1871.543869
Median Absolute Deviation (MAD)1
Skewness-3.327897271
Sum137863536
Variance269434.1262
MonotonicityNot monotonic
2024-03-09T21:10:33.991513image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2018 29642
40.2%
2017 10122
 
13.7%
0 5261
 
7.1%
2019 5251
 
7.1%
2012 2845
 
3.9%
2020 2143
 
2.9%
2013 1995
 
2.7%
2008 1939
 
2.6%
2014 1693
 
2.3%
2015 1693
 
2.3%
Other values (60) 11079
 
15.0%
ValueCountFrequency (%)
0 5261
7.1%
1901 13
 
< 0.1%
1911 1
 
< 0.1%
1917 5
 
< 0.1%
1918 2
 
< 0.1%
ValueCountFrequency (%)
2022 415
 
0.6%
2021 690
 
0.9%
2020 2143
 
2.9%
2019 5251
 
7.1%
2018 29642
40.2%

V11
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.617094064
Minimum0
Maximum12
Zeros5262
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:34.244087image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median8
Q38
95-th percentile10
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.933919109
Coefficient of variation (CV)0.4433848274
Kurtosis0.2787344362
Mean6.617094064
Median Absolute Deviation (MAD)1
Skewness-1.093039211
Sum487435
Variance8.607881338
MonotonicityNot monotonic
2024-03-09T21:10:34.457926image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
8 35203
47.8%
6 7219
 
9.8%
0 5262
 
7.1%
7 5074
 
6.9%
9 4727
 
6.4%
1 4647
 
6.3%
10 2995
 
4.1%
4 1682
 
2.3%
2 1589
 
2.2%
5 1537
 
2.1%
Other values (3) 3728
 
5.1%
ValueCountFrequency (%)
0 5262
7.1%
1 4647
6.3%
2 1589
 
2.2%
3 1245
 
1.7%
4 1682
 
2.3%
ValueCountFrequency (%)
12 1200
 
1.6%
11 1283
 
1.7%
10 2995
 
4.1%
9 4727
 
6.4%
8 35203
47.8%

V12
Real number (ℝ)

ZEROS 

Distinct32
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.62276855
Minimum0
Maximum31
Zeros5261
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:34.679467image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median13
Q320
95-th percentile30
Maximum31
Range31
Interquartile range (IQR)18

Descriptive statistics

Standard deviation9.51697709
Coefficient of variation (CV)0.7539532274
Kurtosis-1.114555482
Mean12.62276855
Median Absolute Deviation (MAD)8
Skewness0.1922785904
Sum929831
Variance90.57285293
MonotonicityNot monotonic
2024-03-09T21:10:34.915049image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 12836
17.4%
13 6612
 
9.0%
20 6594
 
9.0%
0 5261
 
7.1%
21 3455
 
4.7%
17 3029
 
4.1%
31 2648
 
3.6%
10 2465
 
3.3%
7 2159
 
2.9%
14 2154
 
2.9%
Other values (22) 26450
35.9%
ValueCountFrequency (%)
0 5261
7.1%
1 12836
17.4%
2 1297
 
1.8%
3 2153
 
2.9%
4 519
 
0.7%
ValueCountFrequency (%)
31 2648
3.6%
30 1282
1.7%
29 818
 
1.1%
28 995
 
1.4%
27 725
 
1.0%

V13
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.151717959
Minimum0
Maximum24
Zeros5262
Zeros (%)7.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:35.151052image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median6
Q36
95-th percentile6
Maximum24
Range24
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.672778151
Coefficient of variation (CV)0.5188129809
Kurtosis18.46686082
Mean5.151717959
Median Absolute Deviation (MAD)0
Skewness2.590276824
Sum379491
Variance7.143743044
MonotonicityNot monotonic
2024-03-09T21:10:35.373873image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
6 52135
70.8%
3 11314
 
15.4%
0 5262
 
7.1%
2 2386
 
3.2%
4 1253
 
1.7%
22 867
 
1.2%
8 120
 
0.2%
1 85
 
0.1%
5 74
 
0.1%
9 52
 
0.1%
Other values (11) 115
 
0.2%
ValueCountFrequency (%)
0 5262
7.1%
1 85
 
0.1%
2 2386
 
3.2%
3 11314
15.4%
4 1253
 
1.7%
ValueCountFrequency (%)
24 35
 
< 0.1%
23 5
 
< 0.1%
22 867
1.2%
21 22
 
< 0.1%
20 2
 
< 0.1%

V14
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1784206454
Minimum0
Maximum1
Zeros60520
Zeros (%)82.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:35.565451image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.382869049
Coefficient of variation (CV)2.145878624
Kurtosis0.8220376827
Mean0.1784206454
Median Absolute Deviation (MAD)0
Skewness1.679885521
Sum13143
Variance0.1465887087
MonotonicityNot monotonic
2024-03-09T21:10:35.753969image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 60520
82.2%
1 13143
 
17.8%
ValueCountFrequency (%)
0 60520
82.2%
1 13143
 
17.8%
ValueCountFrequency (%)
1 13143
 
17.8%
0 60520
82.2%

V15
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6788211178
Minimum0
Maximum1
Zeros23659
Zeros (%)32.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:35.946787image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4669325086
Coefficient of variation (CV)0.687857959
Kurtosis-1.413342597
Mean0.6788211178
Median Absolute Deviation (MAD)0
Skewness-0.7659606891
Sum50004
Variance0.2180259676
MonotonicityNot monotonic
2024-03-09T21:10:36.146875image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 50004
67.9%
0 23659
32.1%
ValueCountFrequency (%)
0 23659
32.1%
1 50004
67.9%
ValueCountFrequency (%)
1 50004
67.9%
0 23659
32.1%

V16
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04505654128
Minimum0
Maximum1
Zeros70344
Zeros (%)95.5%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:36.346872image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2074295868
Coefficient of variation (CV)4.603761871
Kurtosis17.24276987
Mean0.04505654128
Median Absolute Deviation (MAD)0
Skewness4.386604806
Sum3319
Variance0.04302703347
MonotonicityNot monotonic
2024-03-09T21:10:36.546990image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 70344
95.5%
1 3319
 
4.5%
ValueCountFrequency (%)
0 70344
95.5%
1 3319
 
4.5%
ValueCountFrequency (%)
1 3319
 
4.5%
0 70344
95.5%

V17
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.002226355158
Minimum0
Maximum1
Zeros73499
Zeros (%)99.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:36.738691image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0471320343
Coefficient of variation (CV)21.17004294
Kurtosis444.197097
Mean0.002226355158
Median Absolute Deviation (MAD)0
Skewness21.1230925
Sum164
Variance0.002221428657
MonotonicityNot monotonic
2024-03-09T21:10:36.927266image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 73499
99.8%
1 164
 
0.2%
ValueCountFrequency (%)
0 73499
99.8%
1 164
 
0.2%
ValueCountFrequency (%)
1 164
 
0.2%
0 73499
99.8%

V18
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02431342737
Minimum0
Maximum1
Zeros71872
Zeros (%)97.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:37.116007image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1540214487
Coefficient of variation (CV)6.334830807
Kurtosis36.15699149
Mean0.02431342737
Median Absolute Deviation (MAD)0
Skewness6.177055108
Sum1791
Variance0.02372260666
MonotonicityNot monotonic
2024-03-09T21:10:37.320143image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 71872
97.6%
1 1791
 
2.4%
ValueCountFrequency (%)
0 71872
97.6%
1 1791
 
2.4%
ValueCountFrequency (%)
1 1791
 
2.4%
0 71872
97.6%

E19
Text

MISSING 

Distinct324
Distinct (%)15.1%
Missing71516
Missing (%)97.1%
Memory size1.1 MiB
2024-03-09T21:10:37.648675image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length100
Median length98
Mean length9.443409408
Min length1

Characters and Unicode

Total characters20275
Distinct characters80
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)8.7%

Sample

1st rowModulos
2nd rowMódulos
3rd rowMODULAR
4th rowMODULAR
5th rowModulos
ValueCountFrequency (%)
modulos 674
20.0%
0 383
 
11.4%
módulos 284
 
8.4%
modular 234
 
7.0%
plan 95
 
2.8%
de 91
 
2.7%
22 67
 
2.0%
por 60
 
1.8%
cuatrimestres 56
 
1.7%
años 51
 
1.5%
Other values (235) 1369
40.7%
2024-03-09T21:10:38.322123image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1301
 
6.4%
M 1299
 
6.4%
O 1296
 
6.4%
o 1277
 
6.3%
S 990
 
4.9%
s 950
 
4.7%
L 870
 
4.3%
d 836
 
4.1%
l 792
 
3.9%
U 779
 
3.8%
Other values (70) 9885
48.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 9896
48.8%
Lowercase Letter 8176
40.3%
Space Separator 1301
 
6.4%
Decimal Number 797
 
3.9%
Other Punctuation 45
 
0.2%
Open Punctuation 27
 
0.1%
Close Punctuation 27
 
0.1%
Other Symbol 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%
Control 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1277
15.6%
s 950
11.6%
d 836
10.2%
l 792
9.7%
u 731
8.9%
e 707
8.6%
a 550
6.7%
r 397
 
4.9%
m 347
 
4.2%
i 338
 
4.1%
Other values (21) 1251
15.3%
Uppercase Letter
ValueCountFrequency (%)
M 1299
13.1%
O 1296
13.1%
S 990
10.0%
L 870
8.8%
U 779
7.9%
A 752
7.6%
D 744
7.5%
E 705
7.1%
R 551
 
5.6%
I 425
 
4.3%
Other values (18) 1485
15.0%
Decimal Number
ValueCountFrequency (%)
0 385
48.3%
2 227
28.5%
5 46
 
5.8%
1 42
 
5.3%
9 33
 
4.1%
6 27
 
3.4%
3 18
 
2.3%
4 17
 
2.1%
7 1
 
0.1%
8 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 19
42.2%
, 16
35.6%
/ 9
20.0%
: 1
 
2.2%
Space Separator
ValueCountFrequency (%)
1301
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Other Symbol
ValueCountFrequency (%)
° 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Control
ValueCountFrequency (%)
“ 1
100.0%
Private Use
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 18072
89.1%
Common 2202
 
10.9%
Unknown 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 1299
 
7.2%
O 1296
 
7.2%
o 1277
 
7.1%
S 990
 
5.5%
s 950
 
5.3%
L 870
 
4.8%
d 836
 
4.6%
l 792
 
4.4%
U 779
 
4.3%
A 752
 
4.2%
Other values (49) 8231
45.5%
Common
ValueCountFrequency (%)
1301
59.1%
0 385
 
17.5%
2 227
 
10.3%
5 46
 
2.1%
1 42
 
1.9%
9 33
 
1.5%
( 27
 
1.2%
6 27
 
1.2%
) 27
 
1.2%
. 19
 
0.9%
Other values (10) 68
 
3.1%
Unknown
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19864
98.0%
None 410
 
2.0%
PUA 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1301
 
6.5%
M 1299
 
6.5%
O 1296
 
6.5%
o 1277
 
6.4%
S 990
 
5.0%
s 950
 
4.8%
L 870
 
4.4%
d 836
 
4.2%
l 792
 
4.0%
U 779
 
3.9%
Other values (55) 9474
47.7%
None
ValueCountFrequency (%)
ó 185
45.1%
Ó 134
32.7%
Ñ 32
 
7.8%
ñ 24
 
5.9%
á 8
 
2.0%
é 7
 
1.7%
í 5
 
1.2%
Ò 3
 
0.7%
° 3
 
0.7%
Í 2
 
0.5%
Other values (4) 7
 
1.7%
PUA
ValueCountFrequency (%)
1
100.0%

V20
Real number (ℝ)

ZEROS 

Distinct469
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean254.9546041
Minimum0
Maximum2952
Zeros8983
Zeros (%)12.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:38.593860image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1239
median312
Q3332
95-th percentile360
Maximum2952
Range2952
Interquartile range (IQR)93

Descriptive statistics

Standard deviation124.7655294
Coefficient of variation (CV)0.489363704
Kurtosis3.207312851
Mean254.9546041
Median Absolute Deviation (MAD)34
Skewness-0.9687625132
Sum18780721
Variance15566.43732
MonotonicityNot monotonic
2024-03-09T21:10:38.861031image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
332 15234
20.7%
0 8983
12.2%
278 7432
 
10.1%
324 5165
 
7.0%
312 4288
 
5.8%
276 3472
 
4.7%
338 2566
 
3.5%
320 1907
 
2.6%
360 1470
 
2.0%
239 1438
 
2.0%
Other values (459) 21708
29.5%
ValueCountFrequency (%)
0 8983
12.2%
1 74
 
0.1%
2 10
 
< 0.1%
3 22
 
< 0.1%
4 7
 
< 0.1%
ValueCountFrequency (%)
2952 1
 
< 0.1%
999 8
< 0.1%
984 1
 
< 0.1%
900 2
 
< 0.1%
866 1
 
< 0.1%

V21
Real number (ℝ)

SKEWED  ZEROS 

Distinct614
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.57268914
Minimum0
Maximum40065
Zeros9986
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:39.143245image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median11
Q329
95-th percentile106
Maximum40065
Range40065
Interquartile range (IQR)24

Descriptive statistics

Standard deviation305.3433465
Coefficient of variation (CV)9.67112257
Kurtosis12815.83392
Mean31.57268914
Median Absolute Deviation (MAD)9
Skewness106.5510594
Sum2325739
Variance93234.55926
MonotonicityNot monotonic
2024-03-09T21:10:39.439105image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9986
 
13.6%
6 3064
 
4.2%
5 2997
 
4.1%
7 2861
 
3.9%
8 2831
 
3.8%
4 2813
 
3.8%
9 2501
 
3.4%
3 2399
 
3.3%
10 2397
 
3.3%
11 2234
 
3.0%
Other values (604) 39580
53.7%
ValueCountFrequency (%)
0 9986
13.6%
1 1235
 
1.7%
2 1845
 
2.5%
3 2399
 
3.3%
4 2813
 
3.8%
ValueCountFrequency (%)
40065 1
< 0.1%
39762 1
< 0.1%
35561 1
< 0.1%
34661 1
< 0.1%
13766 1
< 0.1%

V22
Real number (ℝ)

SKEWED  ZEROS 

Distinct652
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.83431302
Minimum0
Maximum71561
Zeros10039
Zeros (%)13.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:39.699693image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median12
Q330
95-th percentile124
Maximum71561
Range71561
Interquartile range (IQR)25

Descriptive statistics

Standard deviation489.6170677
Coefficient of variation (CV)13.66335856
Kurtosis16162.99394
Mean35.83431302
Median Absolute Deviation (MAD)9
Skewness122.8182518
Sum2639663
Variance239724.873
MonotonicityNot monotonic
2024-03-09T21:10:39.953094image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10039
 
13.6%
7 2946
 
4.0%
6 2938
 
4.0%
5 2838
 
3.9%
8 2780
 
3.8%
9 2698
 
3.7%
4 2584
 
3.5%
10 2415
 
3.3%
3 2312
 
3.1%
11 2145
 
2.9%
Other values (642) 39968
54.3%
ValueCountFrequency (%)
0 10039
13.6%
1 1059
 
1.4%
2 1695
 
2.3%
3 2312
 
3.1%
4 2584
 
3.5%
ValueCountFrequency (%)
71561 1
< 0.1%
65650 1
< 0.1%
60983 1
< 0.1%
55945 1
< 0.1%
15783 1
< 0.1%

V23
Real number (ℝ)

SKEWED  ZEROS 

Distinct996
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.40700216
Minimum0
Maximum111626
Zeros9366
Zeros (%)12.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:40.236521image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110
median23
Q358
95-th percentile230
Maximum111626
Range111626
Interquartile range (IQR)48

Descriptive statistics

Standard deviation791.925134
Coefficient of variation (CV)11.74841053
Kurtosis14861.48637
Mean67.40700216
Median Absolute Deviation (MAD)17
Skewness116.7147387
Sum4965402
Variance627145.4178
MonotonicityNot monotonic
2024-03-09T21:10:40.528738image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9366
 
12.7%
12 1689
 
2.3%
11 1607
 
2.2%
14 1583
 
2.1%
10 1579
 
2.1%
13 1573
 
2.1%
16 1553
 
2.1%
15 1551
 
2.1%
18 1491
 
2.0%
17 1451
 
2.0%
Other values (986) 50220
68.2%
ValueCountFrequency (%)
0 9366
12.7%
1 270
 
0.4%
2 326
 
0.4%
3 520
 
0.7%
4 671
 
0.9%
ValueCountFrequency (%)
111626 1
< 0.1%
100745 1
< 0.1%
100311 1
< 0.1%
91506 1
< 0.1%
29549 1
< 0.1%

V24
Real number (ℝ)

SKEWED  ZEROS 

Distinct101
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5837123115
Minimum0
Maximum4437
Zeros67676
Zeros (%)91.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:40.780505image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum4437
Range4437
Interquartile range (IQR)0

Descriptive statistics

Standard deviation24.17638049
Coefficient of variation (CV)41.41831518
Kurtosis25267.64594
Mean0.5837123115
Median Absolute Deviation (MAD)0
Skewness154.9180114
Sum42998
Variance584.4973737
MonotonicityNot monotonic
2024-03-09T21:10:41.048828image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 67676
91.9%
1 2883
 
3.9%
2 989
 
1.3%
3 501
 
0.7%
4 294
 
0.4%
5 204
 
0.3%
6 149
 
0.2%
7 106
 
0.1%
8 105
 
0.1%
10 68
 
0.1%
Other values (91) 688
 
0.9%
ValueCountFrequency (%)
0 67676
91.9%
1 2883
 
3.9%
2 989
 
1.3%
3 501
 
0.7%
4 294
 
0.4%
ValueCountFrequency (%)
4437 1
< 0.1%
3572 1
< 0.1%
3044 1
< 0.1%
387 1
< 0.1%
290 1
< 0.1%

V25
Real number (ℝ)

SKEWED  ZEROS 

Distinct190
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.454285055
Minimum0
Maximum5503
Zeros65897
Zeros (%)89.5%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:41.283177image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile15
Maximum5503
Range5503
Interquartile range (IQR)0

Descriptive statistics

Standard deviation28.27222194
Coefficient of variation (CV)11.51953473
Kurtosis22675.73951
Mean2.454285055
Median Absolute Deviation (MAD)0
Skewness132.7308829
Sum180790
Variance799.3185334
MonotonicityNot monotonic
2024-03-09T21:10:42.305522image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 65897
89.5%
1 910
 
1.2%
2 475
 
0.6%
3 348
 
0.5%
4 285
 
0.4%
5 243
 
0.3%
10 223
 
0.3%
12 218
 
0.3%
8 203
 
0.3%
6 202
 
0.3%
Other values (180) 4659
 
6.3%
ValueCountFrequency (%)
0 65897
89.5%
1 910
 
1.2%
2 475
 
0.6%
3 348
 
0.5%
4 285
 
0.4%
ValueCountFrequency (%)
5503 1
< 0.1%
3203 1
< 0.1%
2420 1
< 0.1%
1886 1
< 0.1%
337 1
< 0.1%

V26
Real number (ℝ)

SKEWED  ZEROS 

Distinct81
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6608202218
Minimum0
Maximum433
Zeros60172
Zeros (%)81.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:42.575551image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum433
Range433
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.993102088
Coefficient of variation (CV)6.04264512
Kurtosis3967.146212
Mean0.6608202218
Median Absolute Deviation (MAD)0
Skewness47.89725896
Sum48678
Variance15.94486429
MonotonicityNot monotonic
2024-03-09T21:10:42.842343image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 60172
81.7%
1 5711
 
7.8%
2 2787
 
3.8%
3 1453
 
2.0%
4 938
 
1.3%
5 623
 
0.8%
6 427
 
0.6%
7 316
 
0.4%
8 237
 
0.3%
9 167
 
0.2%
Other values (71) 832
 
1.1%
ValueCountFrequency (%)
0 60172
81.7%
1 5711
 
7.8%
2 2787
 
3.8%
3 1453
 
2.0%
4 938
 
1.3%
ValueCountFrequency (%)
433 1
< 0.1%
395 1
< 0.1%
273 1
< 0.1%
238 1
< 0.1%
224 1
< 0.1%

V27
Real number (ℝ)

SKEWED  ZEROS 

Distinct100
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.550873573
Minimum0
Maximum9842
Zeros9364
Zeros (%)12.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:43.094112image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile6
Maximum9842
Range9842
Interquartile range (IQR)1

Descriptive statistics

Standard deviation60.43807286
Coefficient of variation (CV)23.69308832
Kurtosis20786.15864
Mean2.550873573
Median Absolute Deviation (MAD)0
Skewness141.3762919
Sum187905
Variance3652.760651
MonotonicityNot monotonic
2024-03-09T21:10:43.372414image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 37646
51.1%
2 10742
 
14.6%
0 9364
 
12.7%
3 5764
 
7.8%
4 3178
 
4.3%
5 2138
 
2.9%
6 1351
 
1.8%
7 814
 
1.1%
8 607
 
0.8%
10 416
 
0.6%
Other values (90) 1643
 
2.2%
ValueCountFrequency (%)
0 9364
 
12.7%
1 37646
51.1%
2 10742
 
14.6%
3 5764
 
7.8%
4 3178
 
4.3%
ValueCountFrequency (%)
9842 1
< 0.1%
9107 1
< 0.1%
7689 1
< 0.1%
5135 1
< 0.1%
1202 1
< 0.1%

V28
Real number (ℝ)

SKEWED  ZEROS 

Distinct559
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.45156999
Minimum0
Maximum23241
Zeros10325
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:43.634454image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q326
95-th percentile95
Maximum23241
Range23241
Interquartile range (IQR)22

Descriptive statistics

Standard deviation148.4727798
Coefficient of variation (CV)5.61300444
Kurtosis13847.79157
Mean26.45156999
Median Absolute Deviation (MAD)8
Skewness105.4429085
Sum1948502
Variance22044.16634
MonotonicityNot monotonic
2024-03-09T21:10:43.886126image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10325
 
14.0%
5 3290
 
4.5%
4 3288
 
4.5%
6 3217
 
4.4%
7 3036
 
4.1%
3 2861
 
3.9%
8 2743
 
3.7%
9 2560
 
3.5%
10 2439
 
3.3%
2 2409
 
3.3%
Other values (549) 37495
50.9%
ValueCountFrequency (%)
0 10325
14.0%
1 1629
 
2.2%
2 2409
 
3.3%
3 2861
 
3.9%
4 3288
 
4.5%
ValueCountFrequency (%)
23241 1
< 0.1%
18994 1
< 0.1%
13612 1
< 0.1%
13568 1
< 0.1%
9364 1
< 0.1%

V29
Real number (ℝ)

SKEWED  ZEROS 

Distinct614
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.27936685
Minimum0
Maximum40236
Zeros10199
Zeros (%)13.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:44.121577image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median11
Q328
95-th percentile118
Maximum40236
Range40236
Interquartile range (IQR)24

Descriptive statistics

Standard deviation249.1639829
Coefficient of variation (CV)7.965761717
Kurtosis16817.65924
Mean31.27936685
Median Absolute Deviation (MAD)9
Skewness122.215758
Sum2304132
Variance62082.6904
MonotonicityNot monotonic
2024-03-09T21:10:44.422184image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10199
 
13.8%
5 3273
 
4.4%
6 3109
 
4.2%
7 3024
 
4.1%
4 2993
 
4.1%
8 2867
 
3.9%
3 2623
 
3.6%
9 2589
 
3.5%
10 2274
 
3.1%
11 2063
 
2.8%
Other values (604) 38649
52.5%
ValueCountFrequency (%)
0 10199
13.8%
1 1329
 
1.8%
2 2027
 
2.8%
3 2623
 
3.6%
4 2993
 
4.1%
ValueCountFrequency (%)
40236 1
< 0.1%
32228 1
< 0.1%
28833 1
< 0.1%
24983 1
< 0.1%
10324 1
< 0.1%

V30
Real number (ℝ)

SKEWED  ZEROS 

Distinct937
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.73093683
Minimum0
Maximum63477
Zeros9492
Zeros (%)12.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:44.697655image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median21
Q354
95-th percentile212
Maximum63477
Range63477
Interquartile range (IQR)45

Descriptive statistics

Standard deviation395.8525871
Coefficient of variation (CV)6.856853687
Kurtosis15817.2627
Mean57.73093683
Median Absolute Deviation (MAD)16
Skewness116.5077145
Sum4252634
Variance156699.2707
MonotonicityNot monotonic
2024-03-09T21:10:44.948894image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9492
 
12.9%
10 1806
 
2.5%
12 1775
 
2.4%
9 1745
 
2.4%
13 1714
 
2.3%
11 1708
 
2.3%
8 1688
 
2.3%
14 1668
 
2.3%
15 1584
 
2.2%
7 1542
 
2.1%
Other values (927) 48941
66.4%
ValueCountFrequency (%)
0 9492
12.9%
1 263
 
0.4%
2 469
 
0.6%
3 692
 
0.9%
4 933
 
1.3%
ValueCountFrequency (%)
63477 1
< 0.1%
51222 1
< 0.1%
42445 1
< 0.1%
38551 1
< 0.1%
19688 1
< 0.1%

V31
Real number (ℝ)

SKEWED  ZEROS 

Distinct109
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4917937092
Minimum0
Maximum2668
Zeros68197
Zeros (%)92.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:45.200482image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum2668
Range2668
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.53910903
Coefficient of variation (CV)29.56343026
Kurtosis23668.45792
Mean0.4917937092
Median Absolute Deviation (MAD)0
Skewness146.6808782
Sum36227
Variance211.3856913
MonotonicityNot monotonic
2024-03-09T21:10:45.488764image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 68197
92.6%
1 2662
 
3.6%
2 893
 
1.2%
3 415
 
0.6%
4 260
 
0.4%
5 182
 
0.2%
6 143
 
0.2%
7 111
 
0.2%
8 95
 
0.1%
11 56
 
0.1%
Other values (99) 649
 
0.9%
ValueCountFrequency (%)
0 68197
92.6%
1 2662
 
3.6%
2 893
 
1.2%
3 415
 
0.6%
4 260
 
0.4%
ValueCountFrequency (%)
2668 1
< 0.1%
2027 1
< 0.1%
1796 1
< 0.1%
282 1
< 0.1%
219 1
< 0.1%

V32
Real number (ℝ)

SKEWED  ZEROS 

Distinct177
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.164777432
Minimum0
Maximum3399
Zeros65979
Zeros (%)89.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:45.740349image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile13
Maximum3399
Range3399
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.59148796
Coefficient of variation (CV)8.588175246
Kurtosis16523.4346
Mean2.164777432
Median Absolute Deviation (MAD)0
Skewness102.8602683
Sum159464
Variance345.6434244
MonotonicityNot monotonic
2024-03-09T21:10:46.023243image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 65979
89.6%
1 926
 
1.3%
2 478
 
0.6%
3 325
 
0.4%
4 313
 
0.4%
5 260
 
0.4%
10 243
 
0.3%
6 237
 
0.3%
9 228
 
0.3%
7 227
 
0.3%
Other values (167) 4447
 
6.0%
ValueCountFrequency (%)
0 65979
89.6%
1 926
 
1.3%
2 478
 
0.6%
3 325
 
0.4%
4 313
 
0.4%
ValueCountFrequency (%)
3399 1
< 0.1%
1454 1
< 0.1%
1426 1
< 0.1%
1361 1
< 0.1%
684 1
< 0.1%

V33
Real number (ℝ)

SKEWED  ZEROS 

Distinct73
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5203833675
Minimum0
Maximum260
Zeros61751
Zeros (%)83.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:46.305641image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum260
Range260
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.047133081
Coefficient of variation (CV)5.855554331
Kurtosis2360.23653
Mean0.5203833675
Median Absolute Deviation (MAD)0
Skewness36.99023399
Sum38333
Variance9.285020015
MonotonicityNot monotonic
2024-03-09T21:10:46.600378image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 61751
83.8%
1 5502
 
7.5%
2 2440
 
3.3%
3 1260
 
1.7%
4 756
 
1.0%
5 515
 
0.7%
6 332
 
0.5%
7 234
 
0.3%
8 168
 
0.2%
9 104
 
0.1%
Other values (63) 601
 
0.8%
ValueCountFrequency (%)
0 61751
83.8%
1 5502
 
7.5%
2 2440
 
3.3%
3 1260
 
1.7%
4 756
 
1.0%
ValueCountFrequency (%)
260 1
< 0.1%
256 1
< 0.1%
210 1
< 0.1%
200 1
< 0.1%
172 1
< 0.1%

V34
Real number (ℝ)

SKEWED  ZEROS 

Distinct89
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.25571861
Minimum0
Maximum4372
Zeros9491
Zeros (%)12.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:46.867599image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile6
Maximum4372
Range4372
Interquartile range (IQR)1

Descriptive statistics

Standard deviation28.75490215
Coefficient of variation (CV)12.74755726
Kurtosis18381.00723
Mean2.25571861
Median Absolute Deviation (MAD)0
Skewness131.9587464
Sum166163
Variance826.8443978
MonotonicityNot monotonic
2024-03-09T21:10:47.188879image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 37539
51.0%
2 10998
 
14.9%
0 9491
 
12.9%
3 5838
 
7.9%
4 3249
 
4.4%
5 2015
 
2.7%
6 1264
 
1.7%
7 797
 
1.1%
8 587
 
0.8%
9 401
 
0.5%
Other values (79) 1484
 
2.0%
ValueCountFrequency (%)
0 9491
 
12.9%
1 37539
51.0%
2 10998
 
14.9%
3 5838
 
7.9%
4 3249
 
4.4%
ValueCountFrequency (%)
4372 1
< 0.1%
4274 1
< 0.1%
3525 1
< 0.1%
2933 1
< 0.1%
569 1
< 0.1%

V35
Real number (ℝ)

SKEWED  ZEROS 

Distinct500
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.68366751
Minimum0
Maximum12571
Zeros16915
Zeros (%)23.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:47.464659image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q322
95-th percentile86
Maximum12571
Range12571
Interquartile range (IQR)21

Descriptive statistics

Standard deviation79.37201586
Coefficient of variation (CV)3.660451619
Kurtosis14033.4973
Mean21.68366751
Median Absolute Deviation (MAD)8
Skewness95.69209715
Sum1597284
Variance6299.916902
MonotonicityNot monotonic
2024-03-09T21:10:47.758280image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16915
23.0%
4 3169
 
4.3%
5 3136
 
4.3%
6 2967
 
4.0%
3 2815
 
3.8%
7 2798
 
3.8%
8 2585
 
3.5%
9 2356
 
3.2%
2 2340
 
3.2%
10 2045
 
2.8%
Other values (490) 32537
44.2%
ValueCountFrequency (%)
0 16915
23.0%
1 1629
 
2.2%
2 2340
 
3.2%
3 2815
 
3.8%
4 3169
 
4.3%
ValueCountFrequency (%)
12571 1
< 0.1%
11279 1
< 0.1%
2033 1
< 0.1%
2021 1
< 0.1%
1897 1
< 0.1%

V36
Real number (ℝ)

SKEWED  ZEROS 

Distinct581
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.10075615
Minimum0
Maximum23440
Zeros16781
Zeros (%)22.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:48.009953image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median9
Q324
95-th percentile108
Maximum23440
Range23440
Interquartile range (IQR)22

Descriptive statistics

Standard deviation128.6278496
Coefficient of variation (CV)4.928127328
Kurtosis23090.34991
Mean26.10075615
Median Absolute Deviation (MAD)9
Skewness135.1893143
Sum1922660
Variance16545.1237
MonotonicityNot monotonic
2024-03-09T21:10:48.295060image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16781
22.8%
5 3088
 
4.2%
4 3035
 
4.1%
6 2847
 
3.9%
7 2784
 
3.8%
3 2573
 
3.5%
8 2511
 
3.4%
9 2313
 
3.1%
10 2050
 
2.8%
2 1963
 
2.7%
Other values (571) 33718
45.8%
ValueCountFrequency (%)
0 16781
22.8%
1 1213
 
1.6%
2 1963
 
2.7%
3 2573
 
3.5%
4 3035
 
4.1%
ValueCountFrequency (%)
23440 1
< 0.1%
20176 1
< 0.1%
2172 1
< 0.1%
2013 1
< 0.1%
1947 1
< 0.1%

V37
Real number (ℝ)

SKEWED  ZEROS 

Distinct869
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.78442366
Minimum0
Maximum36011
Zeros16119
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:48.539094image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median17
Q346
95-th percentile192
Maximum36011
Range36011
Interquartile range (IQR)41

Descriptive statistics

Standard deviation206.6588769
Coefficient of variation (CV)4.324816773
Kurtosis19714.32883
Mean47.78442366
Median Absolute Deviation (MAD)17
Skewness120.9642124
Sum3519944
Variance42707.8914
MonotonicityNot monotonic
2024-03-09T21:10:48.821662image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16119
 
21.9%
10 1747
 
2.4%
12 1721
 
2.3%
9 1700
 
2.3%
11 1642
 
2.2%
8 1617
 
2.2%
7 1593
 
2.2%
13 1531
 
2.1%
14 1530
 
2.1%
15 1443
 
2.0%
Other values (859) 43020
58.4%
ValueCountFrequency (%)
0 16119
21.9%
1 223
 
0.3%
2 430
 
0.6%
3 649
 
0.9%
4 990
 
1.3%
ValueCountFrequency (%)
36011 1
< 0.1%
31455 1
< 0.1%
4063 1
< 0.1%
3961 1
< 0.1%
3883 1
< 0.1%

V38
Real number (ℝ)

SKEWED  ZEROS 

Distinct111
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.391322645
Minimum0
Maximum1852
Zeros69076
Zeros (%)93.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:49.073220image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1852
Range1852
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.92736854
Coefficient of variation (CV)20.25788346
Kurtosis40472.2442
Mean0.391322645
Median Absolute Deviation (MAD)0
Skewness176.5290489
Sum28826
Variance62.84317197
MonotonicityNot monotonic
2024-03-09T21:10:49.359123image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 69076
93.8%
1 2265
 
3.1%
2 710
 
1.0%
3 348
 
0.5%
4 208
 
0.3%
5 140
 
0.2%
6 114
 
0.2%
7 95
 
0.1%
8 72
 
0.1%
9 60
 
0.1%
Other values (101) 575
 
0.8%
ValueCountFrequency (%)
0 69076
93.8%
1 2265
 
3.1%
2 710
 
1.0%
3 348
 
0.5%
4 208
 
0.3%
ValueCountFrequency (%)
1852 1
< 0.1%
240 1
< 0.1%
230 1
< 0.1%
216 1
< 0.1%
195 1
< 0.1%

V39
Real number (ℝ)

SKEWED  ZEROS 

Distinct167
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.930765785
Minimum0
Maximum1854
Zeros66306
Zeros (%)90.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:49.644837image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12
Maximum1854
Range1854
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.31011437
Coefficient of variation (CV)6.893697037
Kurtosis9614.520634
Mean1.930765785
Median Absolute Deviation (MAD)0
Skewness73.206341
Sum142226
Variance177.1591445
MonotonicityNot monotonic
2024-03-09T21:10:49.927812image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 66306
90.0%
1 810
 
1.1%
2 475
 
0.6%
3 321
 
0.4%
5 276
 
0.4%
4 274
 
0.4%
10 267
 
0.4%
6 248
 
0.3%
7 236
 
0.3%
8 230
 
0.3%
Other values (157) 4220
 
5.7%
ValueCountFrequency (%)
0 66306
90.0%
1 810
 
1.1%
2 475
 
0.6%
3 321
 
0.4%
4 274
 
0.4%
ValueCountFrequency (%)
1854 1
< 0.1%
1797 1
< 0.1%
322 1
< 0.1%
274 1
< 0.1%
259 1
< 0.1%

V40
Real number (ℝ)

SKEWED  ZEROS 

Distinct68
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4036626257
Minimum0
Maximum232
Zeros64193
Zeros (%)87.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:50.195162image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum232
Range232
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.658726977
Coefficient of variation (CV)6.58650766
Kurtosis2172.896922
Mean0.4036626257
Median Absolute Deviation (MAD)0
Skewness35.75917761
Sum29735
Variance7.068829136
MonotonicityNot monotonic
2024-03-09T21:10:50.485655image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 64193
87.1%
1 4598
 
6.2%
2 1882
 
2.6%
3 949
 
1.3%
4 590
 
0.8%
5 380
 
0.5%
6 251
 
0.3%
7 136
 
0.2%
8 124
 
0.2%
9 85
 
0.1%
Other values (58) 475
 
0.6%
ValueCountFrequency (%)
0 64193
87.1%
1 4598
 
6.2%
2 1882
 
2.6%
3 949
 
1.3%
4 590
 
0.8%
ValueCountFrequency (%)
232 1
< 0.1%
220 1
< 0.1%
162 1
< 0.1%
147 1
< 0.1%
131 1
< 0.1%

V41
Real number (ℝ)

SKEWED  ZEROS 

Distinct73
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.852463245
Minimum0
Maximum2389
Zeros16117
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:50.753848image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile6
Maximum2389
Range2389
Interquartile range (IQR)1

Descriptive statistics

Standard deviation13.18948079
Coefficient of variation (CV)7.119968954
Kurtosis28024.09673
Mean1.852463245
Median Absolute Deviation (MAD)1
Skewness158.5197772
Sum136458
Variance173.9624036
MonotonicityNot monotonic
2024-03-09T21:10:51.021180image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 33962
46.1%
0 16117
21.9%
2 9297
 
12.6%
3 4677
 
6.3%
4 4126
 
5.6%
5 1674
 
2.3%
6 1134
 
1.5%
7 689
 
0.9%
8 530
 
0.7%
9 333
 
0.5%
Other values (63) 1124
 
1.5%
ValueCountFrequency (%)
0 16117
21.9%
1 33962
46.1%
2 9297
 
12.6%
3 4677
 
6.3%
4 4126
 
5.6%
ValueCountFrequency (%)
2389 1
< 0.1%
2339 1
< 0.1%
480 1
< 0.1%
456 1
< 0.1%
431 1
< 0.1%

V42
Real number (ℝ)

SKEWED  ZEROS 

Distinct35
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0208517166
Minimum0
Maximum128
Zeros73591
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:51.273365image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum128
Range128
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.020585622
Coefficient of variation (CV)48.94492101
Kurtosis6888.600023
Mean0.0208517166
Median Absolute Deviation (MAD)0
Skewness74.80228687
Sum1536
Variance1.041595012
MonotonicityNot monotonic
2024-03-09T21:10:51.547125image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 73591
99.9%
30 6
 
< 0.1%
1 5
 
< 0.1%
5 5
 
< 0.1%
3 5
 
< 0.1%
7 4
 
< 0.1%
6 4
 
< 0.1%
11 4
 
< 0.1%
8 3
 
< 0.1%
4 3
 
< 0.1%
Other values (25) 33
 
< 0.1%
ValueCountFrequency (%)
0 73591
99.9%
1 5
 
< 0.1%
2 1
 
< 0.1%
3 5
 
< 0.1%
4 3
 
< 0.1%
ValueCountFrequency (%)
128 1
< 0.1%
101 1
< 0.1%
84 1
< 0.1%
82 1
< 0.1%
75 1
< 0.1%

V43
Real number (ℝ)

SKEWED  ZEROS 

Distinct37
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02052590853
Minimum0
Maximum142
Zeros73592
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:51.798781image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum142
Range142
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.040901244
Coefficient of variation (CV)50.71157957
Kurtosis8673.254973
Mean0.02052590853
Median Absolute Deviation (MAD)0
Skewness83.00557817
Sum1512
Variance1.083475399
MonotonicityNot monotonic
2024-03-09T21:10:52.034246image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 73592
99.9%
5 6
 
< 0.1%
3 5
 
< 0.1%
2 4
 
< 0.1%
20 3
 
< 0.1%
11 3
 
< 0.1%
6 3
 
< 0.1%
8 3
 
< 0.1%
7 3
 
< 0.1%
4 3
 
< 0.1%
Other values (27) 38
 
0.1%
ValueCountFrequency (%)
0 73592
99.9%
1 2
 
< 0.1%
2 4
 
< 0.1%
3 5
 
< 0.1%
4 3
 
< 0.1%
ValueCountFrequency (%)
142 1
< 0.1%
118 1
< 0.1%
86 1
< 0.1%
71 1
< 0.1%
68 1
< 0.1%

V44
Real number (ℝ)

SKEWED  ZEROS 

Distinct52
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04137762513
Minimum0
Maximum226
Zeros73590
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:53.035230image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum226
Range226
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.025106061
Coefficient of variation (CV)48.94205637
Kurtosis6731.932493
Mean0.04137762513
Median Absolute Deviation (MAD)0
Skewness74.83527223
Sum3048
Variance4.10105456
MonotonicityNot monotonic
2024-03-09T21:10:53.302525image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 73590
99.9%
6 4
 
< 0.1%
15 4
 
< 0.1%
7 3
 
< 0.1%
29 2
 
< 0.1%
47 2
 
< 0.1%
21 2
 
< 0.1%
5 2
 
< 0.1%
3 2
 
< 0.1%
11 2
 
< 0.1%
Other values (42) 50
 
0.1%
ValueCountFrequency (%)
0 73590
99.9%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 2
 
< 0.1%
4 2
 
< 0.1%
ValueCountFrequency (%)
226 1
< 0.1%
219 1
< 0.1%
196 1
< 0.1%
168 1
< 0.1%
146 1
< 0.1%

V45
Real number (ℝ)

SKEWED  ZEROS 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.000990999552
Minimum0
Maximum58
Zeros73661
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:53.505800image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum58
Range58
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2207296116
Coefficient of variation (CV)222.7343202
Kurtosis65005.46233
Mean0.000990999552
Median Absolute Deviation (MAD)0
Skewness250.5504628
Sum73
Variance0.04872156142
MonotonicityNot monotonic
2024-03-09T21:10:53.685833image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 73661
> 99.9%
58 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
0 73661
> 99.9%
15 1
 
< 0.1%
58 1
 
< 0.1%
ValueCountFrequency (%)
58 1
 
< 0.1%
15 1
 
< 0.1%
0 73661
> 99.9%

V46
Real number (ℝ)

SKEWED  ZEROS 

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00628538072
Minimum0
Maximum84
Zeros73650
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:53.905748image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum84
Range84
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5658084016
Coefficient of variation (CV)90.01975008
Kurtosis13077.19103
Mean0.00628538072
Median Absolute Deviation (MAD)0
Skewness108.5803543
Sum463
Variance0.3201391473
MonotonicityNot monotonic
2024-03-09T21:10:54.094501image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 73650
> 99.9%
29 2
 
< 0.1%
15 2
 
< 0.1%
72 1
 
< 0.1%
48 1
 
< 0.1%
53 1
 
< 0.1%
49 1
 
< 0.1%
84 1
 
< 0.1%
35 1
 
< 0.1%
19 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
ValueCountFrequency (%)
0 73650
> 99.9%
7 1
 
< 0.1%
8 1
 
< 0.1%
15 2
 
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
84 1
< 0.1%
72 1
< 0.1%
53 1
< 0.1%
49 1
< 0.1%
48 1
< 0.1%

V47
Real number (ℝ)

SKEWED  ZEROS 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001153903588
Minimum0
Maximum78
Zeros73658
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:54.277589image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum78
Range78
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.287742539
Coefficient of variation (CV)249.3644547
Kurtosis73301.30033
Mean0.001153903588
Median Absolute Deviation (MAD)0
Skewness270.4297199
Sum85
Variance0.08279576876
MonotonicityNot monotonic
2024-03-09T21:10:54.488784image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
0 73658
> 99.9%
1 2
 
< 0.1%
3 1
 
< 0.1%
78 1
 
< 0.1%
2 1
 
< 0.1%
ValueCountFrequency (%)
0 73658
> 99.9%
1 2
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
78 1
 
< 0.1%
ValueCountFrequency (%)
78 1
 
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%
1 2
 
< 0.1%
0 73658
> 99.9%

V48
Real number (ℝ)

SKEWED  ZEROS 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001954848431
Minimum0
Maximum10
Zeros73590
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:54.701221image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0839967216
Coefficient of variation (CV)42.96840627
Kurtosis6167.454221
Mean0.001954848431
Median Absolute Deviation (MAD)0
Skewness69.47791048
Sum144
Variance0.007055449239
MonotonicityNot monotonic
2024-03-09T21:10:54.905658image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 73590
99.9%
1 45
 
0.1%
2 13
 
< 0.1%
3 6
 
< 0.1%
5 4
 
< 0.1%
6 2
 
< 0.1%
10 1
 
< 0.1%
4 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
0 73590
99.9%
1 45
 
0.1%
2 13
 
< 0.1%
3 6
 
< 0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
10 1
 
< 0.1%
9 1
 
< 0.1%
6 2
< 0.1%
5 4
< 0.1%
4 1
 
< 0.1%

V49
Real number (ℝ)

SKEWED  ZEROS 

Distinct1178
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.85626434
Minimum0
Maximum64912
Zeros7013
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:55.141050image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114
median31
Q379
95-th percentile290
Maximum64912
Range64912
Interquartile range (IQR)65

Descriptive statistics

Standard deviation503.8094881
Coefficient of variation (CV)6.080523809
Kurtosis11677.90508
Mean82.85626434
Median Absolute Deviation (MAD)22
Skewness98.66195382
Sum6103441
Variance253824.0003
MonotonicityNot monotonic
2024-03-09T21:10:55.411594image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7013
 
9.5%
15 1278
 
1.7%
16 1251
 
1.7%
17 1248
 
1.7%
14 1233
 
1.7%
20 1227
 
1.7%
19 1216
 
1.7%
13 1200
 
1.6%
22 1195
 
1.6%
21 1194
 
1.6%
Other values (1168) 55608
75.5%
ValueCountFrequency (%)
0 7013
9.5%
1 273
 
0.4%
2 362
 
0.5%
3 493
 
0.7%
4 582
 
0.8%
ValueCountFrequency (%)
64912 1
< 0.1%
60844 1
< 0.1%
58802 1
< 0.1%
58756 1
< 0.1%
22078 1
< 0.1%

V50
Real number (ℝ)

SKEWED  ZEROS 

Distinct1297
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.22959966
Minimum0
Maximum117923
Zeros7090
Zeros (%)9.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:55.665350image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115
median33
Q385
95-th percentile354
Maximum117923
Range117923
Interquartile range (IQR)70

Descriptive statistics

Standard deviation825.0357038
Coefficient of variation (CV)8.573616711
Kurtosis15779.57335
Mean96.22959966
Median Absolute Deviation (MAD)24
Skewness119.6530082
Sum7088561
Variance680683.9125
MonotonicityNot monotonic
2024-03-09T21:10:55.948341image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7090
 
9.6%
19 1275
 
1.7%
16 1260
 
1.7%
17 1248
 
1.7%
15 1227
 
1.7%
13 1212
 
1.6%
18 1204
 
1.6%
22 1200
 
1.6%
20 1170
 
1.6%
23 1147
 
1.6%
Other values (1287) 55630
75.5%
ValueCountFrequency (%)
0 7090
9.6%
1 258
 
0.4%
2 353
 
0.5%
3 453
 
0.6%
4 474
 
0.6%
ValueCountFrequency (%)
117923 1
< 0.1%
116720 1
< 0.1%
96181 1
< 0.1%
93211 1
< 0.1%
22497 1
< 0.1%

V51
Real number (ℝ)

SKEWED  ZEROS 

Distinct1972
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean179.085864
Minimum0
Maximum181632
Zeros6786
Zeros (%)9.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:56.200625image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q131
median64
Q3163
95-th percentile641
Maximum181632
Range181632
Interquartile range (IQR)132

Descriptive statistics

Standard deviation1323.094201
Coefficient of variation (CV)7.388043767
Kurtosis14232.54691
Mean179.085864
Median Absolute Deviation (MAD)45
Skewness112.0675243
Sum13192002
Variance1750578.266
MonotonicityNot monotonic
2024-03-09T21:10:56.491569image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6786
 
9.2%
31 736
 
1.0%
36 703
 
1.0%
32 691
 
0.9%
37 681
 
0.9%
30 656
 
0.9%
38 651
 
0.9%
35 645
 
0.9%
39 643
 
0.9%
40 638
 
0.9%
Other values (1962) 60833
82.6%
ValueCountFrequency (%)
0 6786
9.2%
1 79
 
0.1%
2 93
 
0.1%
3 143
 
0.2%
4 155
 
0.2%
ValueCountFrequency (%)
181632 1
< 0.1%
178767 1
< 0.1%
154983 1
< 0.1%
151967 1
< 0.1%
44575 1
< 0.1%

V52
Real number (ℝ)

SKEWED  ZEROS 

Distinct228
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.762187258
Minimum0
Maximum6692
Zeros63667
Zeros (%)86.4%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:56.759891image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum6692
Range6692
Interquartile range (IQR)0

Descriptive statistics

Standard deviation42.92179323
Coefficient of variation (CV)24.35711247
Kurtosis21048.14428
Mean1.762187258
Median Absolute Deviation (MAD)0
Skewness139.8181859
Sum129808
Variance1842.280334
MonotonicityNot monotonic
2024-03-09T21:10:57.042877image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 63667
86.4%
1 3882
 
5.3%
2 1612
 
2.2%
3 845
 
1.1%
4 522
 
0.7%
5 336
 
0.5%
6 291
 
0.4%
7 185
 
0.3%
8 172
 
0.2%
9 148
 
0.2%
Other values (218) 2003
 
2.7%
ValueCountFrequency (%)
0 63667
86.4%
1 3882
 
5.3%
2 1612
 
2.2%
3 845
 
1.1%
4 522
 
0.7%
ValueCountFrequency (%)
6692 1
< 0.1%
6464 1
< 0.1%
6240 1
< 0.1%
624 1
< 0.1%
564 1
< 0.1%

V53
Real number (ℝ)

SKEWED  ZEROS 

Distinct385
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.558855871
Minimum0
Maximum8902
Zeros64616
Zeros (%)87.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:57.345303image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile42
Maximum8902
Range8902
Interquartile range (IQR)0

Descriptive statistics

Standard deviation55.08288134
Coefficient of variation (CV)8.39824543
Kurtosis12442.6424
Mean6.558855871
Median Absolute Deviation (MAD)0
Skewness92.23406543
Sum483145
Variance3034.123817
MonotonicityNot monotonic
2024-03-09T21:10:57.599650image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 64616
87.7%
1 1043
 
1.4%
2 512
 
0.7%
3 301
 
0.4%
4 243
 
0.3%
6 177
 
0.2%
5 173
 
0.2%
7 152
 
0.2%
8 136
 
0.2%
9 121
 
0.2%
Other values (375) 6189
 
8.4%
ValueCountFrequency (%)
0 64616
87.7%
1 1043
 
1.4%
2 512
 
0.7%
3 301
 
0.4%
4 243
 
0.3%
ValueCountFrequency (%)
8902 1
< 0.1%
5671 1
< 0.1%
5166 1
< 0.1%
4564 1
< 0.1%
1105 1
< 0.1%

V54
Real number (ℝ)

SKEWED  ZEROS 

Distinct148
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.608093616
Minimum0
Maximum761
Zeros54781
Zeros (%)74.4%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:57.884550image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile8
Maximum761
Range761
Interquartile range (IQR)1

Descriptive statistics

Standard deviation9.199183495
Coefficient of variation (CV)5.720552216
Kurtosis2714.969018
Mean1.608093616
Median Absolute Deviation (MAD)0
Skewness40.4710382
Sum118457
Variance84.62497698
MonotonicityNot monotonic
2024-03-09T21:10:58.149300image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 54781
74.4%
1 5689
 
7.7%
2 3382
 
4.6%
3 2133
 
2.9%
4 1420
 
1.9%
5 1016
 
1.4%
6 848
 
1.2%
7 611
 
0.8%
8 517
 
0.7%
9 384
 
0.5%
Other values (138) 2882
 
3.9%
ValueCountFrequency (%)
0 54781
74.4%
1 5689
 
7.7%
2 3382
 
4.6%
3 2133
 
2.9%
4 1420
 
1.9%
ValueCountFrequency (%)
761 1
< 0.1%
757 1
< 0.1%
722 1
< 0.1%
704 1
< 0.1%
595 1
< 0.1%

V55
Real number (ℝ)

SKEWED  ZEROS 

Distinct156
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.661010277
Minimum0
Maximum15770
Zeros7730
Zeros (%)10.5%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:58.453278image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median3
Q36
95-th percentile18
Maximum15770
Range15770
Interquartile range (IQR)3

Descriptive statistics

Standard deviation99.27501364
Coefficient of variation (CV)14.90389738
Kurtosis20663.64335
Mean6.661010277
Median Absolute Deviation (MAD)1
Skewness139.8882091
Sum490670
Variance9855.528333
MonotonicityNot monotonic
2024-03-09T21:10:58.722868image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 31398
42.6%
0 7730
 
10.5%
6 6839
 
9.3%
4 3416
 
4.6%
2 3259
 
4.4%
9 2947
 
4.0%
5 2924
 
4.0%
12 1715
 
2.3%
8 1695
 
2.3%
7 1629
 
2.2%
Other values (146) 10111
 
13.7%
ValueCountFrequency (%)
0 7730
 
10.5%
1 1357
 
1.8%
2 3259
 
4.4%
3 31398
42.6%
4 3416
 
4.6%
ValueCountFrequency (%)
15770 1
< 0.1%
15706 1
< 0.1%
12061 1
< 0.1%
8068 1
< 0.1%
1675 1
< 0.1%

V56
Real number (ℝ)

SKEWED  ZEROS 

Distinct475
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.33874537
Minimum0
Maximum16727
Zeros10738
Zeros (%)14.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:58.990095image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median9
Q321
95-th percentile77
Maximum16727
Range16727
Interquartile range (IQR)18

Descriptive statistics

Standard deviation148.3137334
Coefficient of variation (CV)6.639304534
Kurtosis7280.658627
Mean22.33874537
Median Absolute Deviation (MAD)7
Skewness78.60462431
Sum1645539
Variance21996.96351
MonotonicityNot monotonic
2024-03-09T21:10:59.257452image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10738
 
14.6%
5 3532
 
4.8%
4 3476
 
4.7%
6 3402
 
4.6%
7 3262
 
4.4%
3 3190
 
4.3%
8 3102
 
4.2%
9 2755
 
3.7%
2 2549
 
3.5%
10 2495
 
3.4%
Other values (465) 35162
47.7%
ValueCountFrequency (%)
0 10738
14.6%
1 1940
 
2.6%
2 2549
 
3.5%
3 3190
 
4.3%
4 3476
 
4.7%
ValueCountFrequency (%)
16727 1
< 0.1%
15011 1
< 0.1%
14377 1
< 0.1%
13766 1
< 0.1%
12486 1
< 0.1%

V57
Real number (ℝ)

SKEWED  ZEROS 

Distinct548
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.59593011
Minimum0
Maximum31389
Zeros10492
Zeros (%)14.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:10:59.531865image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q325
95-th percentile98
Maximum31389
Range31389
Interquartile range (IQR)21

Descriptive statistics

Standard deviation232.5801576
Coefficient of variation (CV)8.428060103
Kurtosis11526.28042
Mean27.59593011
Median Absolute Deviation (MAD)8
Skewness100.142229
Sum2032799
Variance54093.52971
MonotonicityNot monotonic
2024-03-09T21:10:59.799247image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10492
 
14.2%
6 3250
 
4.4%
5 3224
 
4.4%
7 3170
 
4.3%
8 2998
 
4.1%
4 2877
 
3.9%
9 2749
 
3.7%
3 2682
 
3.6%
10 2532
 
3.4%
11 2203
 
3.0%
Other values (538) 37486
50.9%
ValueCountFrequency (%)
0 10492
14.2%
1 1367
 
1.9%
2 2033
 
2.8%
3 2682
 
3.6%
4 2877
 
3.9%
ValueCountFrequency (%)
31389 1
< 0.1%
29035 1
< 0.1%
25831 1
< 0.1%
22258 1
< 0.1%
15783 1
< 0.1%

V58
Real number (ℝ)

SKEWED  ZEROS 

Distinct790
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.93467548
Minimum0
Maximum46400
Zeros9698
Zeros (%)13.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:00.066057image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median19
Q346
95-th percentile173
Maximum46400
Range46400
Interquartile range (IQR)37

Descriptive statistics

Standard deviation377.1572966
Coefficient of variation (CV)7.553013872
Kurtosis9562.911975
Mean49.93467548
Median Absolute Deviation (MAD)14
Skewness90.62407044
Sum3678338
Variance142247.6264
MonotonicityNot monotonic
2024-03-09T21:11:00.338915image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9698
 
13.2%
12 1923
 
2.6%
10 1838
 
2.5%
11 1822
 
2.5%
14 1796
 
2.4%
13 1778
 
2.4%
15 1738
 
2.4%
9 1717
 
2.3%
8 1697
 
2.3%
16 1655
 
2.2%
Other values (780) 48001
65.2%
ValueCountFrequency (%)
0 9698
13.2%
1 381
 
0.5%
2 547
 
0.7%
3 768
 
1.0%
4 939
 
1.3%
ValueCountFrequency (%)
46400 1
< 0.1%
45762 1
< 0.1%
40208 1
< 0.1%
32510 1
< 0.1%
29549 1
< 0.1%

V59
Real number (ℝ)

SKEWED  ZEROS 

Distinct80
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3862997706
Minimum0
Maximum2364
Zeros68419
Zeros (%)92.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:00.642318image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum2364
Range2364
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.5369922
Coefficient of variation (CV)29.86538715
Kurtosis28932.40292
Mean0.3862997706
Median Absolute Deviation (MAD)0
Skewness159.3018771
Sum28456
Variance133.1021891
MonotonicityNot monotonic
2024-03-09T21:11:00.912300image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 68419
92.9%
1 2617
 
3.6%
2 860
 
1.2%
3 432
 
0.6%
4 258
 
0.4%
5 187
 
0.3%
6 113
 
0.2%
8 100
 
0.1%
7 79
 
0.1%
9 72
 
0.1%
Other values (70) 526
 
0.7%
ValueCountFrequency (%)
0 68419
92.9%
1 2617
 
3.6%
2 860
 
1.2%
3 432
 
0.6%
4 258
 
0.4%
ValueCountFrequency (%)
2364 1
< 0.1%
1493 1
< 0.1%
1119 1
< 0.1%
299 1
< 0.1%
218 1
< 0.1%

V60
Real number (ℝ)

SKEWED  ZEROS 

Distinct164
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.051396223
Minimum0
Maximum2255
Zeros66254
Zeros (%)89.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:01.190473image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile13
Maximum2255
Range2255
Interquartile range (IQR)0

Descriptive statistics

Standard deviation14.23991603
Coefficient of variation (CV)6.941572705
Kurtosis10205.42666
Mean2.051396223
Median Absolute Deviation (MAD)0
Skewness74.39331204
Sum151112
Variance202.7752086
MonotonicityNot monotonic
2024-03-09T21:11:01.455849image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 66254
89.9%
1 835
 
1.1%
2 472
 
0.6%
3 337
 
0.5%
4 280
 
0.4%
5 236
 
0.3%
10 226
 
0.3%
12 224
 
0.3%
8 222
 
0.3%
6 220
 
0.3%
Other values (154) 4357
 
5.9%
ValueCountFrequency (%)
0 66254
89.9%
1 835
 
1.1%
2 472
 
0.6%
3 337
 
0.5%
4 280
 
0.4%
ValueCountFrequency (%)
2255 1
< 0.1%
1466 1
< 0.1%
789 1
< 0.1%
553 1
< 0.1%
337 1
< 0.1%

V61
Real number (ℝ)

SKEWED  ZEROS 

Distinct74
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5195009706
Minimum0
Maximum225
Zeros61769
Zeros (%)83.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:01.738708image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum225
Range225
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.998627963
Coefficient of variation (CV)5.772131589
Kurtosis1891.234567
Mean0.5195009706
Median Absolute Deviation (MAD)0
Skewness33.31947359
Sum38268
Variance8.991769662
MonotonicityNot monotonic
2024-03-09T21:11:02.000122image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 61769
83.9%
1 5437
 
7.4%
2 2516
 
3.4%
3 1279
 
1.7%
4 747
 
1.0%
5 485
 
0.7%
6 315
 
0.4%
7 225
 
0.3%
8 174
 
0.2%
9 115
 
0.2%
Other values (64) 601
 
0.8%
ValueCountFrequency (%)
0 61769
83.9%
1 5437
 
7.4%
2 2516
 
3.4%
3 1279
 
1.7%
4 747
 
1.0%
ValueCountFrequency (%)
225 1
< 0.1%
224 1
< 0.1%
212 1
< 0.1%
204 1
< 0.1%
168 1
< 0.1%

V62
Real number (ℝ)

SKEWED  ZEROS 

Distinct430
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.46209087
Minimum0
Maximum16372
Zeros10901
Zeros (%)14.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:02.260521image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median8
Q320
95-th percentile71
Maximum16372
Range16372
Interquartile range (IQR)17

Descriptive statistics

Standard deviation96.80250225
Coefficient of variation (CV)4.973900435
Kurtosis16592.35853
Mean19.46209087
Median Absolute Deviation (MAD)7
Skewness114.9922679
Sum1433636
Variance9370.724443
MonotonicityNot monotonic
2024-03-09T21:11:02.548265image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10901
 
14.8%
4 3873
 
5.3%
5 3763
 
5.1%
6 3606
 
4.9%
3 3565
 
4.8%
7 3343
 
4.5%
2 3142
 
4.3%
8 2924
 
4.0%
9 2658
 
3.6%
10 2458
 
3.3%
Other values (420) 33430
45.4%
ValueCountFrequency (%)
0 10901
14.8%
1 2296
 
3.1%
2 3142
 
4.3%
3 3565
 
4.8%
4 3873
 
5.3%
ValueCountFrequency (%)
16372 1
< 0.1%
12541 1
< 0.1%
9407 1
< 0.1%
7631 1
< 0.1%
2550 1
< 0.1%

V63
Real number (ℝ)

SKEWED  ZEROS 

Distinct529
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.41935571
Minimum0
Maximum29110
Zeros10488
Zeros (%)14.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:02.800011image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q324
95-th percentile96
Maximum29110
Range29110
Interquartile range (IQR)20

Descriptive statistics

Standard deviation171.0101764
Coefficient of variation (CV)6.727557468
Kurtosis18154.61536
Mean25.41935571
Median Absolute Deviation (MAD)8
Skewness125.5990689
Sum1872466
Variance29244.48042
MonotonicityNot monotonic
2024-03-09T21:11:03.066760image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10488
 
14.2%
5 3589
 
4.9%
6 3327
 
4.5%
4 3314
 
4.5%
7 3192
 
4.3%
8 3006
 
4.1%
3 2995
 
4.1%
9 2701
 
3.7%
10 2355
 
3.2%
2 2329
 
3.2%
Other values (519) 36367
49.4%
ValueCountFrequency (%)
0 10488
14.2%
1 1571
 
2.1%
2 2329
 
3.2%
3 2995
 
4.1%
4 3314
 
4.5%
ValueCountFrequency (%)
29110 1
< 0.1%
22300 1
< 0.1%
17765 1
< 0.1%
16988 1
< 0.1%
3191 1
< 0.1%

V64
Real number (ℝ)

SKEWED  ZEROS 

Distinct760
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.88144659
Minimum0
Maximum45482
Zeros9683
Zeros (%)13.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:03.339069image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median18
Q344
95-th percentile165
Maximum45482
Range45482
Interquartile range (IQR)36

Descriptive statistics

Standard deviation266.902361
Coefficient of variation (CV)5.946830624
Kurtosis17753.94693
Mean44.88144659
Median Absolute Deviation (MAD)14
Skewness122.5245842
Sum3306102
Variance71236.87032
MonotonicityNot monotonic
2024-03-09T21:11:03.593940image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9683
 
13.1%
10 2013
 
2.7%
9 2007
 
2.7%
8 1948
 
2.6%
12 1917
 
2.6%
11 1915
 
2.6%
13 1887
 
2.6%
7 1861
 
2.5%
14 1833
 
2.5%
15 1777
 
2.4%
Other values (750) 46822
63.6%
ValueCountFrequency (%)
0 9683
13.1%
1 350
 
0.5%
2 649
 
0.9%
3 903
 
1.2%
4 1222
 
1.7%
ValueCountFrequency (%)
45482 1
< 0.1%
34841 1
< 0.1%
27172 1
< 0.1%
24619 1
< 0.1%
5741 1
< 0.1%

V65
Real number (ℝ)

SKEWED  ZEROS 

Distinct83
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3530809226
Minimum0
Maximum1941
Zeros68842
Zeros (%)93.5%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:03.858207image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1941
Range1941
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.964087805
Coefficient of variation (CV)28.22040832
Kurtosis26337.69602
Mean0.3530809226
Median Absolute Deviation (MAD)0
Skewness153.1126722
Sum26009
Variance99.28304578
MonotonicityNot monotonic
2024-03-09T21:11:04.909950image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 68842
93.5%
1 2397
 
3.3%
2 802
 
1.1%
3 371
 
0.5%
4 233
 
0.3%
5 172
 
0.2%
6 116
 
0.2%
7 94
 
0.1%
8 78
 
0.1%
9 63
 
0.1%
Other values (73) 495
 
0.7%
ValueCountFrequency (%)
0 68842
93.5%
1 2397
 
3.3%
2 802
 
1.1%
3 371
 
0.5%
4 233
 
0.3%
ValueCountFrequency (%)
1941 1
< 0.1%
1402 1
< 0.1%
1019 1
< 0.1%
211 1
< 0.1%
133 1
< 0.1%

V66
Real number (ℝ)

SKEWED  ZEROS 

Distinct155
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.872771948
Minimum0
Maximum2404
Zeros66308
Zeros (%)90.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:05.197169image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile12
Maximum2404
Range2404
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.76945785
Coefficient of variation (CV)7.352447724
Kurtosis13275.96043
Mean1.872771948
Median Absolute Deviation (MAD)0
Skewness85.47001114
Sum137954
Variance189.5979694
MonotonicityNot monotonic
2024-03-09T21:11:05.465405image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 66308
90.0%
1 860
 
1.2%
2 451
 
0.6%
3 327
 
0.4%
4 311
 
0.4%
5 261
 
0.4%
7 258
 
0.4%
10 258
 
0.4%
9 238
 
0.3%
6 232
 
0.3%
Other values (145) 4159
 
5.6%
ValueCountFrequency (%)
0 66308
90.0%
1 860
 
1.2%
2 451
 
0.6%
3 327
 
0.4%
4 311
 
0.4%
ValueCountFrequency (%)
2404 1
< 0.1%
921 1
< 0.1%
919 1
< 0.1%
729 1
< 0.1%
565 1
< 0.1%

V67
Real number (ℝ)

SKEWED  ZEROS 

Distinct66
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4166542226
Minimum0
Maximum238
Zeros63099
Zeros (%)85.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:05.734737image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum238
Range238
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.539177557
Coefficient of variation (CV)6.094208146
Kurtosis2675.500399
Mean0.4166542226
Median Absolute Deviation (MAD)0
Skewness38.89918628
Sum30692
Variance6.447422668
MonotonicityNot monotonic
2024-03-09T21:11:05.985862image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 63099
85.7%
1 5186
 
7.0%
2 2205
 
3.0%
3 1091
 
1.5%
4 668
 
0.9%
5 392
 
0.5%
6 250
 
0.3%
7 149
 
0.2%
8 111
 
0.2%
9 75
 
0.1%
Other values (56) 437
 
0.6%
ValueCountFrequency (%)
0 63099
85.7%
1 5186
 
7.0%
2 2205
 
3.0%
3 1091
 
1.5%
4 668
 
0.9%
ValueCountFrequency (%)
238 1
< 0.1%
215 1
< 0.1%
198 1
< 0.1%
135 1
< 0.1%
132 1
< 0.1%

V68
Real number (ℝ)

SKEWED  ZEROS 

Distinct417
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.77539606
Minimum0
Maximum10152
Zeros17294
Zeros (%)23.5%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:06.253889image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q318
95-th percentile71
Maximum10152
Range10152
Interquartile range (IQR)17

Descriptive statistics

Standard deviation62.47178581
Coefficient of variation (CV)3.514508796
Kurtosis17748.12433
Mean17.77539606
Median Absolute Deviation (MAD)7
Skewness112.0891606
Sum1309389
Variance3902.724022
MonotonicityNot monotonic
2024-03-09T21:11:06.548956image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17294
23.5%
4 3506
 
4.8%
5 3273
 
4.4%
3 3147
 
4.3%
6 3123
 
4.2%
7 2905
 
3.9%
2 2799
 
3.8%
8 2688
 
3.6%
9 2419
 
3.3%
10 2141
 
2.9%
Other values (407) 30368
41.2%
ValueCountFrequency (%)
0 17294
23.5%
1 2025
 
2.7%
2 2799
 
3.8%
3 3147
 
4.3%
4 3506
 
4.8%
ValueCountFrequency (%)
10152 1
< 0.1%
9853 1
< 0.1%
1024 1
< 0.1%
1010 1
< 0.1%
870 1
< 0.1%

V69
Real number (ℝ)

SKEWED  ZEROS 

Distinct525
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.03730502
Minimum0
Maximum19089
Zeros16969
Zeros (%)23.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:06.801151image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median8
Q322
95-th percentile95
Maximum19089
Range19089
Interquartile range (IQR)20

Descriptive statistics

Standard deviation107.5599247
Coefficient of variation (CV)4.668945634
Kurtosis23420.00627
Mean23.03730502
Median Absolute Deviation (MAD)8
Skewness137.0960307
Sum1696997
Variance11569.1374
MonotonicityNot monotonic
2024-03-09T21:11:07.083095image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16969
23.0%
5 3259
 
4.4%
4 3163
 
4.3%
6 3019
 
4.1%
7 2901
 
3.9%
3 2744
 
3.7%
8 2590
 
3.5%
9 2328
 
3.2%
2 2142
 
2.9%
10 2063
 
2.8%
Other values (515) 32485
44.1%
ValueCountFrequency (%)
0 16969
23.0%
1 1344
 
1.8%
2 2142
 
2.9%
3 2744
 
3.7%
4 3163
 
4.3%
ValueCountFrequency (%)
19089 1
< 0.1%
17749 1
< 0.1%
1398 1
< 0.1%
1393 1
< 0.1%
1261 1
< 0.1%

V70
Real number (ℝ)

SKEWED  ZEROS 

Distinct754
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.81270108
Minimum0
Maximum29241
Zeros16234
Zeros (%)22.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:07.355650image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median15
Q340
95-th percentile165
Maximum29241
Range29241
Interquartile range (IQR)36

Descriptive statistics

Standard deviation169.338866
Coefficient of variation (CV)4.149170762
Kurtosis21533.40632
Mean40.81270108
Median Absolute Deviation (MAD)15
Skewness128.9884415
Sum3006386
Variance28675.65155
MonotonicityNot monotonic
2024-03-09T21:11:07.623547image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16234
 
22.0%
9 1855
 
2.5%
10 1841
 
2.5%
12 1772
 
2.4%
11 1745
 
2.4%
7 1729
 
2.3%
8 1720
 
2.3%
13 1646
 
2.2%
6 1532
 
2.1%
14 1518
 
2.1%
Other values (744) 42071
57.1%
ValueCountFrequency (%)
0 16234
22.0%
1 284
 
0.4%
2 543
 
0.7%
3 809
 
1.1%
4 1123
 
1.5%
ValueCountFrequency (%)
29241 1
< 0.1%
27602 1
< 0.1%
2417 1
< 0.1%
2408 1
< 0.1%
2094 1
< 0.1%

V71
Real number (ℝ)

SKEWED  ZEROS 

Distinct96
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.317133432
Minimum0
Maximum1539
Zeros69446
Zeros (%)94.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:07.890370image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1539
Range1539
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.453975761
Coefficient of variation (CV)20.35097883
Kurtosis43896.39293
Mean0.317133432
Median Absolute Deviation (MAD)0
Skewness186.5471315
Sum23361
Variance41.65380313
MonotonicityNot monotonic
2024-03-09T21:11:08.157701image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 69446
94.3%
1 2121
 
2.9%
2 637
 
0.9%
3 327
 
0.4%
4 184
 
0.2%
5 124
 
0.2%
6 115
 
0.2%
7 91
 
0.1%
8 64
 
0.1%
10 52
 
0.1%
Other values (86) 502
 
0.7%
ValueCountFrequency (%)
0 69446
94.3%
1 2121
 
2.9%
2 637
 
0.9%
3 327
 
0.4%
4 184
 
0.2%
ValueCountFrequency (%)
1539 1
< 0.1%
141 1
< 0.1%
138 1
< 0.1%
135 1
< 0.1%
132 2
< 0.1%

V72
Real number (ℝ)

SKEWED  ZEROS 

Distinct150
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.773251157
Minimum0
Maximum1563
Zeros66523
Zeros (%)90.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:08.478288image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile11
Maximum1563
Range1563
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.66961428
Coefficient of variation (CV)6.580914518
Kurtosis8050.917824
Mean1.773251157
Median Absolute Deviation (MAD)0
Skewness64.84295709
Sum130623
Variance136.1798976
MonotonicityNot monotonic
2024-03-09T21:11:08.762826image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 66523
90.3%
1 759
 
1.0%
2 467
 
0.6%
3 314
 
0.4%
5 283
 
0.4%
4 274
 
0.4%
10 269
 
0.4%
6 249
 
0.3%
7 237
 
0.3%
8 235
 
0.3%
Other values (140) 4053
 
5.5%
ValueCountFrequency (%)
0 66523
90.3%
1 759
 
1.0%
2 467
 
0.6%
3 314
 
0.4%
4 274
 
0.4%
ValueCountFrequency (%)
1563 1
< 0.1%
1497 1
< 0.1%
322 1
< 0.1%
268 1
< 0.1%
248 1
< 0.1%

V73
Real number (ℝ)

SKEWED  ZEROS 

Distinct63
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3482616782
Minimum0
Maximum189
Zeros64931
Zeros (%)88.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:09.039416image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum189
Range189
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.361603839
Coefficient of variation (CV)6.781118874
Kurtosis1923.657351
Mean0.3482616782
Median Absolute Deviation (MAD)0
Skewness34.39427615
Sum25654
Variance5.577172693
MonotonicityNot monotonic
2024-03-09T21:11:09.438812image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 64931
88.1%
1 4437
 
6.0%
2 1722
 
2.3%
3 856
 
1.2%
4 520
 
0.7%
5 340
 
0.5%
6 194
 
0.3%
7 127
 
0.2%
8 87
 
0.1%
9 67
 
0.1%
Other values (53) 382
 
0.5%
ValueCountFrequency (%)
0 64931
88.1%
1 4437
 
6.0%
2 1722
 
2.3%
3 856
 
1.2%
4 520
 
0.7%
ValueCountFrequency (%)
189 1
< 0.1%
188 1
< 0.1%
140 1
< 0.1%
129 1
< 0.1%
121 1
< 0.1%

V74
Real number (ℝ)

SKEWED  ZEROS 

Distinct33
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01853033409
Minimum0
Maximum128
Zeros73594
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:09.892936image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum128
Range128
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9523674153
Coefficient of variation (CV)51.39504829
Kurtosis8321.916667
Mean0.01853033409
Median Absolute Deviation (MAD)0
Skewness81.77091896
Sum1365
Variance0.9070036938
MonotonicityNot monotonic
2024-03-09T21:11:10.255600image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 73594
99.9%
1 6
 
< 0.1%
30 5
 
< 0.1%
5 5
 
< 0.1%
3 5
 
< 0.1%
7 5
 
< 0.1%
11 5
 
< 0.1%
6 4
 
< 0.1%
8 2
 
< 0.1%
31 2
 
< 0.1%
Other values (23) 30
 
< 0.1%
ValueCountFrequency (%)
0 73594
99.9%
1 6
 
< 0.1%
2 2
 
< 0.1%
3 5
 
< 0.1%
4 2
 
< 0.1%
ValueCountFrequency (%)
128 1
< 0.1%
101 1
< 0.1%
84 1
< 0.1%
79 1
< 0.1%
67 1
< 0.1%

V75
Real number (ℝ)

SKEWED  ZEROS 

Distinct34
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01855748476
Minimum0
Maximum142
Zeros73595
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:10.538936image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum142
Range142
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9849374126
Coefficient of variation (CV)53.0749412
Kurtosis10196.29084
Mean0.01855748476
Median Absolute Deviation (MAD)0
Skewness89.76022534
Sum1367
Variance0.9701017067
MonotonicityNot monotonic
2024-03-09T21:11:10.875291image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 73595
99.9%
5 7
 
< 0.1%
13 4
 
< 0.1%
3 4
 
< 0.1%
1 4
 
< 0.1%
2 3
 
< 0.1%
6 3
 
< 0.1%
8 3
 
< 0.1%
4 3
 
< 0.1%
24 3
 
< 0.1%
Other values (24) 34
 
< 0.1%
ValueCountFrequency (%)
0 73595
99.9%
1 4
 
< 0.1%
2 3
 
< 0.1%
3 4
 
< 0.1%
4 3
 
< 0.1%
ValueCountFrequency (%)
142 1
< 0.1%
118 1
< 0.1%
82 1
< 0.1%
68 1
< 0.1%
60 1
< 0.1%

V76
Real number (ℝ)

SKEWED  ZEROS 

Distinct49
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03708781885
Minimum0
Maximum226
Zeros73593
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:11.155734image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum226
Range226
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.899023941
Coefficient of variation (CV)51.20344091
Kurtosis7970.388458
Mean0.03708781885
Median Absolute Deviation (MAD)0
Skewness81.05494573
Sum2732
Variance3.606291929
MonotonicityNot monotonic
2024-03-09T21:11:11.439029image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0 73593
99.9%
6 4
 
< 0.1%
29 3
 
< 0.1%
19 3
 
< 0.1%
2 3
 
< 0.1%
7 3
 
< 0.1%
12 3
 
< 0.1%
11 2
 
< 0.1%
47 2
 
< 0.1%
48 2
 
< 0.1%
Other values (39) 45
 
0.1%
ValueCountFrequency (%)
0 73593
99.9%
1 1
 
< 0.1%
2 3
 
< 0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
ValueCountFrequency (%)
226 1
< 0.1%
219 1
< 0.1%
196 1
< 0.1%
161 1
< 0.1%
118 1
< 0.1%

V77
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.715067266 × 10-5
Minimum0
Maximum2
Zeros73662
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:11.674778image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.007368944654
Coefficient of variation (CV)271.409285
Kurtosis73663
Mean2.715067266 × 10-5
Median Absolute Deviation (MAD)0
Skewness271.409285
Sum2
Variance5.430134532 × 10-5
MonotonicityNot monotonic
2024-03-09T21:11:11.878968image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 73662
> 99.9%
2 1
 
< 0.1%
ValueCountFrequency (%)
0 73662
> 99.9%
2 1
 
< 0.1%
ValueCountFrequency (%)
2 1
 
< 0.1%
0 73662
> 99.9%

V78
Real number (ℝ)

SKEWED  ZEROS 

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.005959572648
Minimum0
Maximum84
Zeros73650
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:12.146364image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum84
Range84
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5404089277
Coefficient of variation (CV)90.67914087
Kurtosis14421.92049
Mean0.005959572648
Median Absolute Deviation (MAD)0
Skewness112.8912979
Sum439
Variance0.2920418092
MonotonicityNot monotonic
2024-03-09T21:11:12.355644image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 73650
> 99.9%
29 2
 
< 0.1%
15 2
 
< 0.1%
72 1
 
< 0.1%
46 1
 
< 0.1%
48 1
 
< 0.1%
32 1
 
< 0.1%
84 1
 
< 0.1%
35 1
 
< 0.1%
19 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
ValueCountFrequency (%)
0 73650
> 99.9%
7 1
 
< 0.1%
8 1
 
< 0.1%
15 2
 
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
84 1
< 0.1%
72 1
< 0.1%
48 1
< 0.1%
46 1
< 0.1%
35 1
< 0.1%

V79
Real number (ℝ)

SKEWED  ZEROS 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001153903588
Minimum0
Maximum78
Zeros73658
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:12.645835image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum78
Range78
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.287742539
Coefficient of variation (CV)249.3644547
Kurtosis73301.30033
Mean0.001153903588
Median Absolute Deviation (MAD)0
Skewness270.4297199
Sum85
Variance0.08279576876
MonotonicityNot monotonic
2024-03-09T21:11:12.901863image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
0 73658
> 99.9%
1 2
 
< 0.1%
3 1
 
< 0.1%
78 1
 
< 0.1%
2 1
 
< 0.1%
ValueCountFrequency (%)
0 73658
> 99.9%
1 2
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
78 1
 
< 0.1%
ValueCountFrequency (%)
78 1
 
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%
1 2
 
< 0.1%
0 73658
> 99.9%

V80
Real number (ℝ)

SKEWED  ZEROS 

Distinct887
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.59476264
Minimum0
Maximum34271
Zeros8169
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:13.174283image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q111
median26
Q360
95-th percentile214
Maximum34271
Range34271
Interquartile range (IQR)49

Descriptive statistics

Standard deviation271.3054621
Coefficient of variation (CV)4.552505121
Kurtosis9248.201713
Mean59.59476264
Median Absolute Deviation (MAD)19
Skewness84.97010965
Sum4389929
Variance73606.65375
MonotonicityNot monotonic
2024-03-09T21:11:13.528287image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8169
 
11.1%
15 1459
 
2.0%
14 1423
 
1.9%
12 1391
 
1.9%
16 1375
 
1.9%
18 1373
 
1.9%
17 1372
 
1.9%
13 1346
 
1.8%
11 1332
 
1.8%
19 1311
 
1.8%
Other values (877) 53112
72.1%
ValueCountFrequency (%)
0 8169
11.1%
1 362
 
0.5%
2 524
 
0.7%
3 661
 
0.9%
4 803
 
1.1%
ValueCountFrequency (%)
34271 1
< 0.1%
30749 1
< 0.1%
29268 1
< 0.1%
28035 1
< 0.1%
13766 1
< 0.1%

V81
Real number (ℝ)

SKEWED  ZEROS 

Distinct1066
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.07114834
Minimum0
Maximum66903
Zeros8211
Zeros (%)11.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:13.880758image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113
median29
Q372
95-th percentile285
Maximum66903
Range66903
Interquartile range (IQR)59

Descriptive statistics

Standard deviation465.8391533
Coefficient of variation (CV)6.123729739
Kurtosis13714.74896
Mean76.07114834
Median Absolute Deviation (MAD)21
Skewness108.7216518
Sum5603629
Variance217006.1168
MonotonicityNot monotonic
2024-03-09T21:11:14.152302image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8211
 
11.1%
17 1345
 
1.8%
16 1335
 
1.8%
15 1313
 
1.8%
13 1303
 
1.8%
19 1298
 
1.8%
18 1291
 
1.8%
20 1269
 
1.7%
23 1199
 
1.6%
12 1197
 
1.6%
Other values (1056) 53902
73.2%
ValueCountFrequency (%)
0 8211
11.1%
1 280
 
0.4%
2 371
 
0.5%
3 492
 
0.7%
4 553
 
0.8%
ValueCountFrequency (%)
66903 1
< 0.1%
58335 1
< 0.1%
54941 1
< 0.1%
51335 1
< 0.1%
15783 1
< 0.1%

V82
Real number (ℝ)

SKEWED  ZEROS 

Distinct1595
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.665911
Minimum0
Maximum101174
Zeros7895
Zeros (%)10.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:14.456607image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126
median55
Q3132
95-th percentile498
Maximum101174
Range101174
Interquartile range (IQR)106

Descriptive statistics

Standard deviation732.9720023
Coefficient of variation (CV)5.402772127
Kurtosis12082.94386
Mean135.665911
Median Absolute Deviation (MAD)39
Skewness100.2947882
Sum9993558
Variance537247.9562
MonotonicityNot monotonic
2024-03-09T21:11:14.776553image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7895
 
10.7%
31 754
 
1.0%
32 740
 
1.0%
36 728
 
1.0%
34 721
 
1.0%
30 719
 
1.0%
27 710
 
1.0%
33 697
 
0.9%
37 697
 
0.9%
29 688
 
0.9%
Other values (1585) 59314
80.5%
ValueCountFrequency (%)
0 7895
10.7%
1 88
 
0.1%
2 106
 
0.1%
3 163
 
0.2%
4 188
 
0.3%
ValueCountFrequency (%)
101174 1
< 0.1%
86370 1
< 0.1%
85690 1
< 0.1%
80603 1
< 0.1%
29549 1
< 0.1%

V83
Real number (ℝ)

SKEWED  ZEROS 

Distinct168
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.056541276
Minimum0
Maximum3766
Zeros65063
Zeros (%)88.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:15.122285image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum3766
Range3766
Interquartile range (IQR)0

Descriptive statistics

Standard deviation24.44930643
Coefficient of variation (CV)23.14089093
Kurtosis19854.3048
Mean1.056541276
Median Absolute Deviation (MAD)0
Skewness134.0654979
Sum77828
Variance597.768585
MonotonicityNot monotonic
2024-03-09T21:11:15.438945image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 65063
88.3%
1 3603
 
4.9%
2 1475
 
2.0%
3 733
 
1.0%
4 468
 
0.6%
5 299
 
0.4%
6 228
 
0.3%
8 168
 
0.2%
7 149
 
0.2%
9 117
 
0.2%
Other values (158) 1360
 
1.8%
ValueCountFrequency (%)
0 65063
88.3%
1 3603
 
4.9%
2 1475
 
2.0%
3 733
 
1.0%
4 468
 
0.6%
ValueCountFrequency (%)
3766 1
< 0.1%
3677 1
< 0.1%
3434 1
< 0.1%
476 1
< 0.1%
454 1
< 0.1%

V84
Real number (ℝ)

SKEWED  ZEROS 

Distinct348
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.703378901
Minimum0
Maximum4659
Zeros65028
Zeros (%)88.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:15.675154image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile38
Maximum4659
Range4659
Interquartile range (IQR)0

Descriptive statistics

Standard deviation36.10449126
Coefficient of variation (CV)6.330368697
Kurtosis5418.69873
Mean5.703378901
Median Absolute Deviation (MAD)0
Skewness52.56039421
Sum420128
Variance1303.534289
MonotonicityNot monotonic
2024-03-09T21:11:15.927353image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 65028
88.3%
1 960
 
1.3%
2 474
 
0.6%
3 281
 
0.4%
4 226
 
0.3%
6 180
 
0.2%
5 159
 
0.2%
8 141
 
0.2%
7 135
 
0.2%
9 117
 
0.2%
Other values (338) 5962
 
8.1%
ValueCountFrequency (%)
0 65028
88.3%
1 960
 
1.3%
2 474
 
0.6%
3 281
 
0.4%
4 226
 
0.3%
ValueCountFrequency (%)
4659 1
< 0.1%
3273 1
< 0.1%
2779 1
< 0.1%
2385 1
< 0.1%
861 1
< 0.1%

V85
Real number (ℝ)

SKEWED  ZEROS 

Distinct128
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.285570775
Minimum0
Maximum631
Zeros56456
Zeros (%)76.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:16.188586image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum631
Range631
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.475783112
Coefficient of variation (CV)5.815147059
Kurtosis2401.186763
Mean1.285570775
Median Absolute Deviation (MAD)0
Skewness37.82804639
Sum94699
Variance55.88733313
MonotonicityNot monotonic
2024-03-09T21:11:16.472336image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 56456
76.6%
1 5552
 
7.5%
2 3272
 
4.4%
3 1931
 
2.6%
4 1325
 
1.8%
5 919
 
1.2%
6 757
 
1.0%
7 522
 
0.7%
8 441
 
0.6%
9 338
 
0.5%
Other values (118) 2150
 
2.9%
ValueCountFrequency (%)
0 56456
76.6%
1 5552
 
7.5%
2 3272
 
4.4%
3 1931
 
2.6%
4 1325
 
1.8%
ValueCountFrequency (%)
631 1
< 0.1%
627 1
< 0.1%
550 1
< 0.1%
464 1
< 0.1%
424 1
< 0.1%

V86
Real number (ℝ)

SKEWED  ZEROS 

Distinct373
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.233590812
Minimum0
Maximum25054
Zeros39956
Zeros (%)54.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:16.739352image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile36
Maximum25054
Range25054
Interquartile range (IQR)6

Descriptive statistics

Standard deviation179.093416
Coefficient of variation (CV)19.39585798
Kurtosis16314.02348
Mean9.233590812
Median Absolute Deviation (MAD)0
Skewness124.7039165
Sum680174
Variance32074.45165
MonotonicityNot monotonic
2024-03-09T21:11:17.014243image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39956
54.2%
1 4638
 
6.3%
2 3576
 
4.9%
3 2789
 
3.8%
4 2306
 
3.1%
5 1899
 
2.6%
6 1606
 
2.2%
7 1323
 
1.8%
8 1130
 
1.5%
9 1003
 
1.4%
Other values (363) 13437
 
18.2%
ValueCountFrequency (%)
0 39956
54.2%
1 4638
 
6.3%
2 3576
 
4.9%
3 2789
 
3.8%
4 2306
 
3.1%
ValueCountFrequency (%)
25054 1
< 0.1%
24409 1
< 0.1%
23035 1
< 0.1%
21184 1
< 0.1%
8620 1
< 0.1%

V87
Real number (ℝ)

SKEWED  ZEROS 

Distinct324
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.237812742
Minimum0
Maximum43392
Zeros43253
Zeros (%)58.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:18.050933image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile28
Maximum43392
Range43392
Interquartile range (IQR)3

Descriptive statistics

Standard deviation275.3982913
Coefficient of variation (CV)33.43099678
Kurtosis18912.71709
Mean8.237812742
Median Absolute Deviation (MAD)0
Skewness134.7250736
Sum606822
Variance75844.21884
MonotonicityNot monotonic
2024-03-09T21:11:18.318794image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43253
58.7%
1 5554
 
7.5%
2 3841
 
5.2%
3 2769
 
3.8%
4 2073
 
2.8%
5 1655
 
2.2%
6 1442
 
2.0%
7 1099
 
1.5%
8 937
 
1.3%
9 840
 
1.1%
Other values (314) 10200
 
13.8%
ValueCountFrequency (%)
0 43253
58.7%
1 5554
 
7.5%
2 3841
 
5.2%
3 2769
 
3.8%
4 2073
 
2.8%
ValueCountFrequency (%)
43392 1
< 0.1%
40172 1
< 0.1%
31948 1
< 0.1%
30114 1
< 0.1%
8648 1
< 0.1%

V88
Real number (ℝ)

SKEWED  ZEROS 

Distinct548
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.47140355
Minimum0
Maximum67801
Zeros37786
Zeros (%)51.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:18.595468image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q39
95-th percentile63
Maximum67801
Range67801
Interquartile range (IQR)9

Descriptive statistics

Standard deviation453.3761356
Coefficient of variation (CV)25.94961156
Kurtosis17781.30647
Mean17.47140355
Median Absolute Deviation (MAD)0
Skewness130.6349669
Sum1286996
Variance205549.9203
MonotonicityNot monotonic
2024-03-09T21:11:18.905685image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37786
51.3%
1 3705
 
5.0%
2 2821
 
3.8%
3 2419
 
3.3%
4 2054
 
2.8%
5 1760
 
2.4%
6 1481
 
2.0%
7 1360
 
1.8%
8 1195
 
1.6%
9 1017
 
1.4%
Other values (538) 18065
24.5%
ValueCountFrequency (%)
0 37786
51.3%
1 3705
 
5.0%
2 2821
 
3.8%
3 2419
 
3.3%
4 2054
 
2.8%
ValueCountFrequency (%)
67801 1
< 0.1%
65226 1
< 0.1%
54983 1
< 0.1%
51298 1
< 0.1%
17268 1
< 0.1%

V89
Real number (ℝ)

SKEWED  ZEROS 

Distinct63
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1974125409
Minimum0
Maximum2079
Zeros71708
Zeros (%)97.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:19.347182image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2079
Range2079
Interquartile range (IQR)0

Descriptive statistics

Standard deviation13.04337308
Coefficient of variation (CV)66.07165394
Kurtosis23854.70369
Mean0.1974125409
Median Absolute Deviation (MAD)0
Skewness153.1612378
Sum14542
Variance170.1295814
MonotonicityNot monotonic
2024-03-09T21:11:19.638955image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71708
97.3%
1 968
 
1.3%
2 342
 
0.5%
3 148
 
0.2%
4 103
 
0.1%
5 68
 
0.1%
6 41
 
0.1%
9 31
 
< 0.1%
8 30
 
< 0.1%
7 30
 
< 0.1%
Other values (53) 194
 
0.3%
ValueCountFrequency (%)
0 71708
97.3%
1 968
 
1.3%
2 342
 
0.5%
3 148
 
0.2%
4 103
 
0.1%
ValueCountFrequency (%)
2079 1
< 0.1%
2073 1
< 0.1%
1925 1
< 0.1%
165 1
< 0.1%
139 1
< 0.1%

V90
Real number (ℝ)

SKEWED  ZEROS 

Distinct79
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4028888316
Minimum0
Maximum3248
Zeros70684
Zeros (%)96.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:19.902669image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3248
Range3248
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15.86497964
Coefficient of variation (CV)39.37805766
Kurtosis27976.78877
Mean0.4028888316
Median Absolute Deviation (MAD)0
Skewness157.1705447
Sum29678
Variance251.697579
MonotonicityNot monotonic
2024-03-09T21:11:20.172315image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 70684
96.0%
1 738
 
1.0%
2 445
 
0.6%
3 299
 
0.4%
4 219
 
0.3%
5 184
 
0.2%
6 129
 
0.2%
7 115
 
0.2%
8 91
 
0.1%
9 88
 
0.1%
Other values (69) 671
 
0.9%
ValueCountFrequency (%)
0 70684
96.0%
1 738
 
1.0%
2 445
 
0.6%
3 299
 
0.4%
4 219
 
0.3%
ValueCountFrequency (%)
3248 1
< 0.1%
1737 1
< 0.1%
1631 1
< 0.1%
1333 1
< 0.1%
240 1
< 0.1%

V91
Real number (ℝ)

SKEWED  ZEROS 

Distinct39
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1413328265
Minimum0
Maximum246
Zeros69525
Zeros (%)94.4%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:20.522497image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum246
Range246
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.530559813
Coefficient of variation (CV)10.82947147
Kurtosis13829.04579
Mean0.1413328265
Median Absolute Deviation (MAD)0
Skewness96.30295992
Sum10411
Variance2.342613341
MonotonicityNot monotonic
2024-03-09T21:11:20.822562image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 69525
94.4%
1 2217
 
3.0%
2 872
 
1.2%
3 370
 
0.5%
4 234
 
0.3%
5 129
 
0.2%
6 100
 
0.1%
7 46
 
0.1%
9 34
 
< 0.1%
8 27
 
< 0.1%
Other values (29) 109
 
0.1%
ValueCountFrequency (%)
0 69525
94.4%
1 2217
 
3.0%
2 872
 
1.2%
3 370
 
0.5%
4 234
 
0.3%
ValueCountFrequency (%)
246 1
< 0.1%
208 1
< 0.1%
78 1
< 0.1%
54 1
< 0.1%
49 1
< 0.1%

V92
Real number (ℝ)

SKEWED  ZEROS 

Distinct319
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.988691745
Minimum0
Maximum8100
Zeros41313
Zeros (%)56.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:21.105743image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile30
Maximum8100
Range8100
Interquartile range (IQR)5

Descriptive statistics

Standard deviation59.78850818
Coefficient of variation (CV)8.555035816
Kurtosis10541.44675
Mean6.988691745
Median Absolute Deviation (MAD)0
Skewness92.78838341
Sum514808
Variance3574.665711
MonotonicityNot monotonic
2024-03-09T21:11:21.501190image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41313
56.1%
1 4996
 
6.8%
2 3579
 
4.9%
3 2741
 
3.7%
4 2247
 
3.1%
5 1775
 
2.4%
6 1599
 
2.2%
7 1289
 
1.7%
8 1151
 
1.6%
9 958
 
1.3%
Other values (309) 12015
 
16.3%
ValueCountFrequency (%)
0 41313
56.1%
1 4996
 
6.8%
2 3579
 
4.9%
3 2741
 
3.7%
4 2247
 
3.1%
ValueCountFrequency (%)
8100 1
< 0.1%
6869 1
< 0.1%
6453 1
< 0.1%
5981 1
< 0.1%
4161 1
< 0.1%

V93
Real number (ℝ)

SKEWED  ZEROS 

Distinct283
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.858965831
Minimum0
Maximum11845
Zeros44578
Zeros (%)60.5%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:21.855637image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile25
Maximum11845
Range11845
Interquartile range (IQR)3

Descriptive statistics

Standard deviation85.65044987
Coefficient of variation (CV)14.61869762
Kurtosis13658.65568
Mean5.858965831
Median Absolute Deviation (MAD)0
Skewness111.9702015
Sum431589
Variance7335.999563
MonotonicityNot monotonic
2024-03-09T21:11:22.125505image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44578
60.5%
1 5970
 
8.1%
2 3913
 
5.3%
3 2588
 
3.5%
4 1993
 
2.7%
5 1603
 
2.2%
6 1269
 
1.7%
7 1013
 
1.4%
8 886
 
1.2%
9 810
 
1.1%
Other values (273) 9040
 
12.3%
ValueCountFrequency (%)
0 44578
60.5%
1 5970
 
8.1%
2 3913
 
5.3%
3 2588
 
3.5%
4 1993
 
2.7%
ValueCountFrequency (%)
11845 1
< 0.1%
11126 1
< 0.1%
9928 1
< 0.1%
9026 1
< 0.1%
7218 1
< 0.1%

V94
Real number (ℝ)

SKEWED  ZEROS 

Distinct472
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.84765758
Minimum0
Maximum17995
Zeros38879
Zeros (%)52.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:22.397430image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q38
95-th percentile54
Maximum17995
Range17995
Interquartile range (IQR)8

Descriptive statistics

Standard deviation143.9712462
Coefficient of variation (CV)11.20603077
Kurtosis12065.23854
Mean12.84765758
Median Absolute Deviation (MAD)0
Skewness103.6400093
Sum946397
Variance20727.71973
MonotonicityNot monotonic
2024-03-09T21:11:22.722258image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38879
52.8%
1 4124
 
5.6%
2 3105
 
4.2%
3 2421
 
3.3%
4 2006
 
2.7%
5 1692
 
2.3%
6 1478
 
2.0%
7 1345
 
1.8%
8 1111
 
1.5%
9 1037
 
1.4%
Other values (462) 16465
22.4%
ValueCountFrequency (%)
0 38879
52.8%
1 4124
 
5.6%
2 3105
 
4.2%
3 2421
 
3.3%
4 2006
 
2.7%
ValueCountFrequency (%)
17995 1
< 0.1%
17826 1
< 0.1%
17126 1
< 0.1%
16381 1
< 0.1%
11379 1
< 0.1%

V95
Real number (ℝ)

SKEWED  ZEROS 

Distinct60
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1386992113
Minimum0
Maximum777
Zeros71877
Zeros (%)97.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:22.990417image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum777
Range777
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.830838178
Coefficient of variation (CV)34.82960093
Kurtosis19858.68032
Mean0.1386992113
Median Absolute Deviation (MAD)0
Skewness133.4660058
Sum10217
Variance23.3369975
MonotonicityNot monotonic
2024-03-09T21:11:23.230084image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71877
97.6%
1 871
 
1.2%
2 305
 
0.4%
3 138
 
0.2%
4 93
 
0.1%
5 65
 
0.1%
6 51
 
0.1%
7 35
 
< 0.1%
9 21
 
< 0.1%
10 19
 
< 0.1%
Other values (50) 188
 
0.3%
ValueCountFrequency (%)
0 71877
97.6%
1 871
 
1.2%
2 305
 
0.4%
3 138
 
0.2%
4 93
 
0.1%
ValueCountFrequency (%)
777 1
< 0.1%
727 1
< 0.1%
625 1
< 0.1%
117 1
< 0.1%
109 1
< 0.1%

V96
Real number (ℝ)

SKEWED  ZEROS 

Distinct74
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2920054844
Minimum0
Maximum995
Zeros70751
Zeros (%)96.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:23.472359image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum995
Range995
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.653271315
Coefficient of variation (CV)19.36015457
Kurtosis17734.12589
Mean0.2920054844
Median Absolute Deviation (MAD)0
Skewness118.5558924
Sum21510
Variance31.95947656
MonotonicityNot monotonic
2024-03-09T21:11:23.873593image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 70751
96.0%
1 821
 
1.1%
2 457
 
0.6%
3 287
 
0.4%
4 204
 
0.3%
6 157
 
0.2%
5 154
 
0.2%
7 106
 
0.1%
8 100
 
0.1%
9 77
 
0.1%
Other values (64) 549
 
0.7%
ValueCountFrequency (%)
0 70751
96.0%
1 821
 
1.1%
2 457
 
0.6%
3 287
 
0.4%
4 204
 
0.3%
ValueCountFrequency (%)
995 1
< 0.1%
697 1
< 0.1%
533 1
< 0.1%
442 1
< 0.1%
121 1
< 0.1%

V97
Real number (ℝ)

SKEWED  ZEROS 

Distinct35
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1037291449
Minimum0
Maximum89
Zeros70279
Zeros (%)95.4%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:24.155535image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum89
Range89
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9089768107
Coefficient of variation (CV)8.762983746
Kurtosis2757.219577
Mean0.1037291449
Median Absolute Deviation (MAD)0
Skewness38.78293331
Sum7641
Variance0.8262388423
MonotonicityNot monotonic
2024-03-09T21:11:24.388747image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 70279
95.4%
1 1975
 
2.7%
2 659
 
0.9%
3 283
 
0.4%
4 161
 
0.2%
5 92
 
0.1%
6 61
 
0.1%
7 39
 
0.1%
8 25
 
< 0.1%
9 18
 
< 0.1%
Other values (25) 71
 
0.1%
ValueCountFrequency (%)
0 70279
95.4%
1 1975
 
2.7%
2 659
 
0.9%
3 283
 
0.4%
4 161
 
0.2%
ValueCountFrequency (%)
89 1
< 0.1%
85 1
< 0.1%
41 2
< 0.1%
40 1
< 0.1%
39 1
< 0.1%

V98
Real number (ℝ)

SKEWED  ZEROS 

Distinct228
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.90717185
Minimum0
Maximum2419
Zeros49602
Zeros (%)67.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:24.655734image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile18
Maximum2419
Range2419
Interquartile range (IQR)2

Descriptive statistics

Standard deviation23.18062993
Coefficient of variation (CV)5.93284115
Kurtosis3158.41173
Mean3.90717185
Median Absolute Deviation (MAD)0
Skewness45.53483631
Sum287814
Variance537.3416041
MonotonicityNot monotonic
2024-03-09T21:11:24.929497image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49602
67.3%
1 4473
 
6.1%
2 3002
 
4.1%
3 2222
 
3.0%
4 1747
 
2.4%
5 1407
 
1.9%
6 1141
 
1.5%
7 999
 
1.4%
8 836
 
1.1%
9 742
 
1.0%
Other values (218) 7492
 
10.2%
ValueCountFrequency (%)
0 49602
67.3%
1 4473
 
6.1%
2 3002
 
4.1%
3 2222
 
3.0%
4 1747
 
2.4%
ValueCountFrequency (%)
2419 1
< 0.1%
1503 1
< 0.1%
1426 1
< 0.1%
1422 1
< 0.1%
1399 1
< 0.1%

V99
Real number (ℝ)

SKEWED  ZEROS 

Distinct216
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.062202191
Minimum0
Maximum4351
Zeros52761
Zeros (%)71.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:25.180795image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile14
Maximum4351
Range4351
Interquartile range (IQR)1

Descriptive statistics

Standard deviation24.65089889
Coefficient of variation (CV)8.050055923
Kurtosis14714.7218
Mean3.062202191
Median Absolute Deviation (MAD)0
Skewness96.68341085
Sum225571
Variance607.6668159
MonotonicityNot monotonic
2024-03-09T21:11:25.455414image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 52761
71.6%
1 4984
 
6.8%
2 3039
 
4.1%
3 1970
 
2.7%
4 1522
 
2.1%
5 1139
 
1.5%
6 957
 
1.3%
7 762
 
1.0%
8 662
 
0.9%
9 542
 
0.7%
Other values (206) 5325
 
7.2%
ValueCountFrequency (%)
0 52761
71.6%
1 4984
 
6.8%
2 3039
 
4.1%
3 1970
 
2.7%
4 1522
 
2.1%
ValueCountFrequency (%)
4351 1
< 0.1%
2427 1
< 0.1%
1098 1
< 0.1%
1025 1
< 0.1%
1006 1
< 0.1%

V100
Real number (ℝ)

SKEWED  ZEROS 

Distinct355
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.969374041
Minimum0
Maximum6770
Zeros47403
Zeros (%)64.4%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:25.706201image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile32
Maximum6770
Range6770
Interquartile range (IQR)3

Descriptive statistics

Standard deviation46.63739898
Coefficient of variation (CV)6.691762948
Kurtosis7364.451665
Mean6.969374041
Median Absolute Deviation (MAD)0
Skewness66.27977742
Sum513385
Variance2175.046984
MonotonicityNot monotonic
2024-03-09T21:11:25.988627image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47403
64.4%
1 4034
 
5.5%
2 2670
 
3.6%
3 1977
 
2.7%
4 1651
 
2.2%
5 1344
 
1.8%
6 1144
 
1.6%
7 968
 
1.3%
8 865
 
1.2%
9 749
 
1.0%
Other values (345) 10858
 
14.7%
ValueCountFrequency (%)
0 47403
64.4%
1 4034
 
5.5%
2 2670
 
3.6%
3 1977
 
2.7%
4 1651
 
2.2%
ValueCountFrequency (%)
6770 1
< 0.1%
3853 1
< 0.1%
2497 1
< 0.1%
2478 1
< 0.1%
2447 1
< 0.1%

V101
Real number (ℝ)

SKEWED  ZEROS 

Distinct48
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07418921304
Minimum0
Maximum313
Zeros72509
Zeros (%)98.4%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:26.256114image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum313
Range313
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.859242612
Coefficient of variation (CV)25.06082132
Kurtosis12783.85646
Mean0.07418921304
Median Absolute Deviation (MAD)0
Skewness93.88544366
Sum5465
Variance3.45678309
MonotonicityNot monotonic
2024-03-09T21:11:26.541758image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 72509
98.4%
1 585
 
0.8%
2 187
 
0.3%
3 99
 
0.1%
4 60
 
0.1%
5 38
 
0.1%
7 22
 
< 0.1%
6 19
 
< 0.1%
11 12
 
< 0.1%
8 12
 
< 0.1%
Other values (38) 120
 
0.2%
ValueCountFrequency (%)
0 72509
98.4%
1 585
 
0.8%
2 187
 
0.3%
3 99
 
0.1%
4 60
 
0.1%
ValueCountFrequency (%)
313 1
< 0.1%
149 1
< 0.1%
148 1
< 0.1%
134 1
< 0.1%
114 1
< 0.1%

V102
Real number (ℝ)

SKEWED  ZEROS 

Distinct59
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1575146274
Minimum0
Maximum357
Zeros71566
Zeros (%)97.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:26.827834image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum357
Range357
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.305498531
Coefficient of variation (CV)14.63672656
Kurtosis9617.090868
Mean0.1575146274
Median Absolute Deviation (MAD)0
Skewness75.93972971
Sum11603
Variance5.315323474
MonotonicityNot monotonic
2024-03-09T21:11:27.100730image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71566
97.2%
1 684
 
0.9%
2 351
 
0.5%
3 214
 
0.3%
4 168
 
0.2%
5 132
 
0.2%
6 85
 
0.1%
7 75
 
0.1%
8 61
 
0.1%
9 41
 
0.1%
Other values (49) 286
 
0.4%
ValueCountFrequency (%)
0 71566
97.2%
1 684
 
0.9%
2 351
 
0.5%
3 214
 
0.3%
4 168
 
0.2%
ValueCountFrequency (%)
357 1
< 0.1%
234 1
< 0.1%
136 1
< 0.1%
100 1
< 0.1%
85 1
< 0.1%

V103
Real number (ℝ)

SKEWED  ZEROS 

Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05540094756
Minimum0
Maximum44
Zeros71689
Zeros (%)97.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:27.355579image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum44
Range44
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5658901987
Coefficient of variation (CV)10.21444982
Kurtosis1318.862766
Mean0.05540094756
Median Absolute Deviation (MAD)0
Skewness28.65502947
Sum4081
Variance0.3202317169
MonotonicityNot monotonic
2024-03-09T21:11:27.599344image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 71689
97.3%
1 1239
 
1.7%
2 362
 
0.5%
3 156
 
0.2%
4 73
 
0.1%
5 43
 
0.1%
6 18
 
< 0.1%
8 17
 
< 0.1%
7 15
 
< 0.1%
9 10
 
< 0.1%
Other values (17) 41
 
0.1%
ValueCountFrequency (%)
0 71689
97.3%
1 1239
 
1.7%
2 362
 
0.5%
3 156
 
0.2%
4 73
 
0.1%
ValueCountFrequency (%)
44 1
< 0.1%
33 1
< 0.1%
31 1
< 0.1%
29 1
< 0.1%
28 1
< 0.1%

V104
Real number (ℝ)

SKEWED  ZEROS 

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.002321382512
Minimum0
Maximum45
Zeros73648
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:27.829892image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum45
Range45
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2554449818
Coefficient of variation (CV)110.0400216
Kurtosis21815.45613
Mean0.002321382512
Median Absolute Deviation (MAD)0
Skewness142.3579164
Sum171
Variance0.06525213874
MonotonicityNot monotonic
2024-03-09T21:11:28.018049image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 73648
> 99.9%
2 5
 
< 0.1%
45 1
 
< 0.1%
35 1
 
< 0.1%
3 1
 
< 0.1%
10 1
 
< 0.1%
14 1
 
< 0.1%
5 1
 
< 0.1%
1 1
 
< 0.1%
33 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
ValueCountFrequency (%)
0 73648
> 99.9%
1 1
 
< 0.1%
2 5
 
< 0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
45 1
< 0.1%
35 1
< 0.1%
33 1
< 0.1%
14 1
< 0.1%
10 1
< 0.1%

V105
Real number (ℝ)

SKEWED  ZEROS 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001968423768
Minimum0
Maximum65
Zeros73648
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:28.206697image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum65
Range65
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2672902735
Coefficient of variation (CV)135.7889891
Kurtosis48938.08224
Mean0.001968423768
Median Absolute Deviation (MAD)0
Skewness210.8436693
Sum145
Variance0.07144409028
MonotonicityNot monotonic
2024-03-09T21:11:28.439197image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 73648
> 99.9%
3 3
 
< 0.1%
1 2
 
< 0.1%
2 2
 
< 0.1%
5 2
 
< 0.1%
65 1
 
< 0.1%
11 1
 
< 0.1%
4 1
 
< 0.1%
7 1
 
< 0.1%
27 1
 
< 0.1%
ValueCountFrequency (%)
0 73648
> 99.9%
1 2
 
< 0.1%
2 2
 
< 0.1%
3 3
 
< 0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
65 1
< 0.1%
27 1
< 0.1%
11 1
< 0.1%
7 1
< 0.1%
6 1
< 0.1%

V106
Real number (ℝ)

SKEWED  ZEROS 

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00428980628
Minimum0
Maximum110
Zeros73646
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:28.672202image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum110
Range110
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5066772575
Coefficient of variation (CV)118.1119203
Kurtosis33791.28888
Mean0.00428980628
Median Absolute Deviation (MAD)0
Skewness173.1711623
Sum316
Variance0.2567218433
MonotonicityNot monotonic
2024-03-09T21:11:28.889115image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 73646
> 99.9%
5 3
 
< 0.1%
3 2
 
< 0.1%
7 2
 
< 0.1%
17 2
 
< 0.1%
110 1
 
< 0.1%
4 1
 
< 0.1%
46 1
 
< 0.1%
2 1
 
< 0.1%
1 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
ValueCountFrequency (%)
0 73646
> 99.9%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 2
 
< 0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
110 1
< 0.1%
60 1
< 0.1%
46 1
< 0.1%
17 2
< 0.1%
15 1
< 0.1%

V107
Real number (ℝ)

SKEWED  ZEROS 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0009638488794
Minimum0
Maximum56
Zeros73661
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:29.057740image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum56
Range56
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2136033609
Coefficient of variation (CV)221.6149912
Kurtosis64460.10375
Mean0.0009638488794
Median Absolute Deviation (MAD)0
Skewness249.316863
Sum71
Variance0.04562639579
MonotonicityNot monotonic
2024-03-09T21:11:29.232180image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 73661
> 99.9%
56 1
 
< 0.1%
15 1
 
< 0.1%
ValueCountFrequency (%)
0 73661
> 99.9%
15 1
 
< 0.1%
56 1
 
< 0.1%
ValueCountFrequency (%)
56 1
 
< 0.1%
15 1
 
< 0.1%
0 73661
> 99.9%

V108
Real number (ℝ)

SKEWED  ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0003258080719
Minimum0
Maximum17
Zeros73660
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:29.424031image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum17
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.06570319174
Coefficient of variation (CV)201.6622589
Kurtosis61306.54756
Mean0.0003258080719
Median Absolute Deviation (MAD)0
Skewness241.5068079
Sum24
Variance0.004316909405
MonotonicityNot monotonic
2024-03-09T21:11:29.632891image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 73660
> 99.9%
2 1
 
< 0.1%
5 1
 
< 0.1%
17 1
 
< 0.1%
ValueCountFrequency (%)
0 73660
> 99.9%
2 1
 
< 0.1%
5 1
 
< 0.1%
17 1
 
< 0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
5 1
 
< 0.1%
2 1
 
< 0.1%
0 73660
> 99.9%

V109
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros73663
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:29.833564image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2024-03-09T21:11:30.021674image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 73663
100.0%
ValueCountFrequency (%)
0 73663
100.0%
ValueCountFrequency (%)
0 73663
100.0%

V110
Real number (ℝ)

SKEWED  ZEROS 

Distinct588
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.13177579
Minimum0
Maximum32809
Zeros34757
Zeros (%)47.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:30.242074image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q313
95-th percentile82
Maximum32809
Range32809
Interquartile range (IQR)13

Descriptive statistics

Standard deviation242.4023397
Coefficient of variation (CV)12.0407828
Kurtosis13723.23334
Mean20.13177579
Median Absolute Deviation (MAD)1
Skewness111.7388453
Sum1482967
Variance58758.89427
MonotonicityNot monotonic
2024-03-09T21:11:30.533341image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34757
47.2%
1 3701
 
5.0%
2 2825
 
3.8%
3 2229
 
3.0%
4 1790
 
2.4%
5 1619
 
2.2%
6 1421
 
1.9%
7 1254
 
1.7%
8 1247
 
1.7%
9 1092
 
1.5%
Other values (578) 21728
29.5%
ValueCountFrequency (%)
0 34757
47.2%
1 3701
 
5.0%
2 2825
 
3.8%
3 2229
 
3.0%
4 1790
 
2.4%
ValueCountFrequency (%)
32809 1
< 0.1%
30641 1
< 0.1%
29488 1
< 0.1%
28053 1
< 0.1%
16720 1
< 0.1%

V111
Real number (ℝ)

SKEWED  ZEROS 

Distinct559
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.16094919
Minimum0
Maximum59588
Zeros37574
Zeros (%)51.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:30.804445image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q38
95-th percentile66
Maximum59588
Range59588
Interquartile range (IQR)8

Descriptive statistics

Standard deviation370.4977614
Coefficient of variation (CV)21.58958443
Kurtosis17873.79479
Mean17.16094919
Median Absolute Deviation (MAD)0
Skewness129.4923111
Sum1264127
Variance137268.5912
MonotonicityNot monotonic
2024-03-09T21:11:31.056234image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37574
51.0%
1 4596
 
6.2%
2 3210
 
4.4%
3 2544
 
3.5%
4 2019
 
2.7%
5 1652
 
2.2%
6 1530
 
2.1%
7 1251
 
1.7%
8 1073
 
1.5%
9 1010
 
1.4%
Other values (549) 17204
23.4%
ValueCountFrequency (%)
0 37574
51.0%
1 4596
 
6.2%
2 3210
 
4.4%
3 2544
 
3.5%
4 2019
 
2.7%
ValueCountFrequency (%)
59588 1
< 0.1%
49817 1
< 0.1%
41876 1
< 0.1%
41240 1
< 0.1%
17674 1
< 0.1%

V112
Real number (ℝ)

SKEWED  ZEROS 

Distinct924
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.29272498
Minimum0
Maximum92397
Zeros33122
Zeros (%)45.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:32.208774image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q322
95-th percentile147
Maximum92397
Range92397
Interquartile range (IQR)22

Descriptive statistics

Standard deviation610.222656
Coefficient of variation (CV)16.36304819
Kurtosis16153.98371
Mean37.29272498
Median Absolute Deviation (MAD)2
Skewness122.6201765
Sum2747094
Variance372371.6899
MonotonicityNot monotonic
2024-03-09T21:11:32.481132image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 33122
45.0%
1 2804
 
3.8%
2 2356
 
3.2%
3 1898
 
2.6%
4 1570
 
2.1%
5 1356
 
1.8%
6 1187
 
1.6%
7 1113
 
1.5%
8 1038
 
1.4%
9 953
 
1.3%
Other values (914) 26266
35.7%
ValueCountFrequency (%)
0 33122
45.0%
1 2804
 
3.8%
2 2356
 
3.2%
3 1898
 
2.6%
4 1570
 
2.1%
ValueCountFrequency (%)
92397 1
< 0.1%
80458 1
< 0.1%
71364 1
< 0.1%
69293 1
< 0.1%
34394 1
< 0.1%

V113
Real number (ℝ)

SKEWED  ZEROS 

Distinct111
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4112648141
Minimum0
Maximum3015
Zeros70582
Zeros (%)95.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:32.740308image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3015
Range3015
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.56042401
Coefficient of variation (CV)45.13010444
Kurtosis22593.92296
Mean0.4112648141
Median Absolute Deviation (MAD)0
Skewness147.0145832
Sum30295
Variance344.4893396
MonotonicityNot monotonic
2024-03-09T21:11:33.007106image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 70582
95.8%
1 1315
 
1.8%
2 498
 
0.7%
3 256
 
0.3%
4 195
 
0.3%
5 120
 
0.2%
6 88
 
0.1%
8 62
 
0.1%
7 56
 
0.1%
9 53
 
0.1%
Other values (101) 438
 
0.6%
ValueCountFrequency (%)
0 70582
95.8%
1 1315
 
1.8%
2 498
 
0.7%
3 256
 
0.3%
4 195
 
0.3%
ValueCountFrequency (%)
3015 1
< 0.1%
2806 1
< 0.1%
2698 1
< 0.1%
254 1
< 0.1%
215 1
< 0.1%

V114
Real number (ℝ)

SKEWED  ZEROS 

Distinct146
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8527347515
Minimum0
Maximum4243
Zeros69624
Zeros (%)94.5%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:33.290351image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum4243
Range4243
Interquartile range (IQR)0

Descriptive statistics

Standard deviation22.35097489
Coefficient of variation (CV)26.2109347
Kurtosis22401.76923
Mean0.8527347515
Median Absolute Deviation (MAD)0
Skewness139.0031722
Sum62815
Variance499.5660784
MonotonicityNot monotonic
2024-03-09T21:11:33.564194image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 69624
94.5%
1 857
 
1.2%
2 462
 
0.6%
3 337
 
0.5%
4 254
 
0.3%
5 204
 
0.3%
6 161
 
0.2%
8 135
 
0.2%
7 132
 
0.2%
9 102
 
0.1%
Other values (136) 1395
 
1.9%
ValueCountFrequency (%)
0 69624
94.5%
1 857
 
1.2%
2 462
 
0.6%
3 337
 
0.5%
4 254
 
0.3%
ValueCountFrequency (%)
4243 1
< 0.1%
2398 1
< 0.1%
2387 1
< 0.1%
2179 1
< 0.1%
338 1
< 0.1%

V115
Real number (ℝ)

SKEWED  ZEROS 

Distinct66
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.300462919
Minimum0
Maximum368
Zeros67523
Zeros (%)91.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:33.842942image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum368
Range368
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.644896477
Coefficient of variation (CV)8.802738407
Kurtosis6758.345005
Mean0.300462919
Median Absolute Deviation (MAD)0
Skewness61.60426835
Sum22133
Variance6.995477373
MonotonicityNot monotonic
2024-03-09T21:11:34.113374image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 67523
91.7%
1 2726
 
3.7%
2 1227
 
1.7%
3 641
 
0.9%
4 363
 
0.5%
5 263
 
0.4%
6 190
 
0.3%
7 137
 
0.2%
8 102
 
0.1%
10 81
 
0.1%
Other values (56) 410
 
0.6%
ValueCountFrequency (%)
0 67523
91.7%
1 2726
 
3.7%
2 1227
 
1.7%
3 641
 
0.9%
4 363
 
0.5%
ValueCountFrequency (%)
368 1
< 0.1%
258 1
< 0.1%
163 1
< 0.1%
134 1
< 0.1%
100 1
< 0.1%

V116
Real number (ℝ)

SKEWED  ZEROS 

Distinct179
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.157758983
Minimum0
Maximum899
Zeros49912
Zeros (%)67.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:34.399625image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile16
Maximum899
Range899
Interquartile range (IQR)2

Descriptive statistics

Standard deviation11.63303916
Coefficient of variation (CV)3.683954103
Kurtosis1083.809091
Mean3.157758983
Median Absolute Deviation (MAD)0
Skewness22.17805949
Sum232610
Variance135.3276002
MonotonicityNot monotonic
2024-03-09T21:11:34.655736image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49912
67.8%
1 3726
 
5.1%
2 3091
 
4.2%
3 2384
 
3.2%
4 1932
 
2.6%
5 1667
 
2.3%
6 1244
 
1.7%
7 1077
 
1.5%
8 903
 
1.2%
9 782
 
1.1%
Other values (169) 6945
 
9.4%
ValueCountFrequency (%)
0 49912
67.8%
1 3726
 
5.1%
2 3091
 
4.2%
3 2384
 
3.2%
4 1932
 
2.6%
ValueCountFrequency (%)
899 1
< 0.1%
790 1
< 0.1%
541 1
< 0.1%
534 1
< 0.1%
442 1
< 0.1%

V117
Real number (ℝ)

SKEWED  ZEROS 

Distinct179
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.512278892
Minimum0
Maximum1293
Zeros52464
Zeros (%)71.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:34.924696image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile13
Maximum1293
Range1293
Interquartile range (IQR)1

Descriptive statistics

Standard deviation11.51397851
Coefficient of variation (CV)4.583081339
Kurtosis3168.911554
Mean2.512278892
Median Absolute Deviation (MAD)0
Skewness38.25359741
Sum185062
Variance132.5717011
MonotonicityNot monotonic
2024-03-09T21:11:35.207751image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 52464
71.2%
1 4358
 
5.9%
2 3147
 
4.3%
3 2217
 
3.0%
4 1674
 
2.3%
5 1358
 
1.8%
6 1062
 
1.4%
7 863
 
1.2%
8 785
 
1.1%
9 617
 
0.8%
Other values (169) 5118
 
6.9%
ValueCountFrequency (%)
0 52464
71.2%
1 4358
 
5.9%
2 3147
 
4.3%
3 2217
 
3.0%
4 1674
 
2.3%
ValueCountFrequency (%)
1293 1
< 0.1%
935 1
< 0.1%
754 1
< 0.1%
562 1
< 0.1%
479 1
< 0.1%

V118
Real number (ℝ)

SKEWED  ZEROS 

Distinct274
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.670037875
Minimum0
Maximum2083
Zeros48328
Zeros (%)65.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:35.480105image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile29
Maximum2083
Range2083
Interquartile range (IQR)3

Descriptive statistics

Standard deviation22.62088608
Coefficient of variation (CV)3.989547616
Kurtosis1901.457933
Mean5.670037875
Median Absolute Deviation (MAD)0
Skewness29.21611173
Sum417672
Variance511.7044873
MonotonicityNot monotonic
2024-03-09T21:11:35.764453image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 48328
65.6%
1 2642
 
3.6%
2 2316
 
3.1%
3 1989
 
2.7%
4 1763
 
2.4%
5 1538
 
2.1%
6 1289
 
1.7%
7 1105
 
1.5%
8 964
 
1.3%
9 817
 
1.1%
Other values (264) 10912
 
14.8%
ValueCountFrequency (%)
0 48328
65.6%
1 2642
 
3.6%
2 2316
 
3.1%
3 1989
 
2.7%
4 1763
 
2.4%
ValueCountFrequency (%)
2083 1
< 0.1%
1834 1
< 0.1%
1288 1
< 0.1%
1103 1
< 0.1%
884 1
< 0.1%

V119
Real number (ℝ)

SKEWED  ZEROS 

Distinct31
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03864898253
Minimum0
Maximum99
Zeros72724
Zeros (%)98.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:35.999930image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum99
Range99
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.707893167
Coefficient of variation (CV)18.31595868
Kurtosis6720.465776
Mean0.03864898253
Median Absolute Deviation (MAD)0
Skewness63.27149111
Sum2847
Variance0.5011127358
MonotonicityNot monotonic
2024-03-09T21:11:36.234807image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 72724
98.7%
1 525
 
0.7%
2 142
 
0.2%
3 86
 
0.1%
4 38
 
0.1%
6 27
 
< 0.1%
5 27
 
< 0.1%
7 16
 
< 0.1%
8 12
 
< 0.1%
9 11
 
< 0.1%
Other values (21) 55
 
0.1%
ValueCountFrequency (%)
0 72724
98.7%
1 525
 
0.7%
2 142
 
0.2%
3 86
 
0.1%
4 38
 
0.1%
ValueCountFrequency (%)
99 1
< 0.1%
66 1
< 0.1%
35 1
< 0.1%
33 1
< 0.1%
32 2
< 0.1%

V120
Real number (ℝ)

SKEWED  ZEROS 

Distinct51
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1261284498
Minimum0
Maximum240
Zeros72131
Zeros (%)97.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:36.492656image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum240
Range240
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.694745182
Coefficient of variation (CV)13.43666067
Kurtosis6139.786642
Mean0.1261284498
Median Absolute Deviation (MAD)0
Skewness55.61048776
Sum9291
Variance2.872161231
MonotonicityNot monotonic
2024-03-09T21:11:36.781681image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 72131
97.9%
1 393
 
0.5%
2 252
 
0.3%
3 180
 
0.2%
4 126
 
0.2%
5 85
 
0.1%
6 68
 
0.1%
7 59
 
0.1%
8 51
 
0.1%
9 39
 
0.1%
Other values (41) 279
 
0.4%
ValueCountFrequency (%)
0 72131
97.9%
1 393
 
0.5%
2 252
 
0.3%
3 180
 
0.2%
4 126
 
0.2%
ValueCountFrequency (%)
240 1
< 0.1%
119 1
< 0.1%
95 1
< 0.1%
67 1
< 0.1%
61 1
< 0.1%

V121
Real number (ℝ)

SKEWED  ZEROS 

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03851322917
Minimum0
Maximum37
Zeros72073
Zeros (%)97.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:37.017287image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum37
Range37
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3936336306
Coefficient of variation (CV)10.22073815
Kurtosis1796.133538
Mean0.03851322917
Median Absolute Deviation (MAD)0
Skewness30.69952854
Sum2837
Variance0.1549474352
MonotonicityNot monotonic
2024-03-09T21:11:37.236606image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 72073
97.8%
1 1048
 
1.4%
2 305
 
0.4%
3 109
 
0.1%
4 49
 
0.1%
5 22
 
< 0.1%
6 18
 
< 0.1%
7 8
 
< 0.1%
8 7
 
< 0.1%
10 6
 
< 0.1%
Other values (10) 18
 
< 0.1%
ValueCountFrequency (%)
0 72073
97.8%
1 1048
 
1.4%
2 305
 
0.4%
3 109
 
0.1%
4 49
 
0.1%
ValueCountFrequency (%)
37 1
< 0.1%
26 1
< 0.1%
22 1
< 0.1%
19 1
< 0.1%
18 1
< 0.1%

V122
Real number (ℝ)

SKEWED  ZEROS 

Distinct166
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.916511682
Minimum0
Maximum4195
Zeros49906
Zeros (%)67.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:37.510000image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile14
Maximum4195
Range4195
Interquartile range (IQR)2

Descriptive statistics

Standard deviation20.86821962
Coefficient of variation (CV)7.155198366
Kurtosis22863.19741
Mean2.916511682
Median Absolute Deviation (MAD)0
Skewness124.9046904
Sum214839
Variance435.48259
MonotonicityNot monotonic
2024-03-09T21:11:37.794340image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49906
67.7%
1 4169
 
5.7%
2 3323
 
4.5%
3 2560
 
3.5%
4 1980
 
2.7%
5 1634
 
2.2%
6 1285
 
1.7%
7 1091
 
1.5%
8 931
 
1.3%
9 746
 
1.0%
Other values (156) 6038
 
8.2%
ValueCountFrequency (%)
0 49906
67.7%
1 4169
 
5.7%
2 3323
 
4.5%
3 2560
 
3.5%
4 1980
 
2.7%
ValueCountFrequency (%)
4195 1
< 0.1%
1346 1
< 0.1%
1194 1
< 0.1%
1089 1
< 0.1%
1041 1
< 0.1%

V123
Real number (ℝ)

SKEWED  ZEROS 

Distinct160
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.356461181
Minimum0
Maximum5014
Zeros52643
Zeros (%)71.5%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:38.108553image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile11
Maximum5014
Range5014
Interquartile range (IQR)1

Descriptive statistics

Standard deviation23.62954523
Coefficient of variation (CV)10.02755548
Kurtosis29157.73856
Mean2.356461181
Median Absolute Deviation (MAD)0
Skewness150.0369022
Sum173584
Variance558.3554077
MonotonicityNot monotonic
2024-03-09T21:11:38.409952image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 52643
71.5%
1 4906
 
6.7%
2 3278
 
4.4%
3 2261
 
3.1%
4 1684
 
2.3%
5 1361
 
1.8%
6 1034
 
1.4%
7 787
 
1.1%
8 664
 
0.9%
9 545
 
0.7%
Other values (150) 4500
 
6.1%
ValueCountFrequency (%)
0 52643
71.5%
1 4906
 
6.7%
2 3278
 
4.4%
3 2261
 
3.1%
4 1684
 
2.3%
ValueCountFrequency (%)
5014 1
< 0.1%
2285 1
< 0.1%
1794 1
< 0.1%
804 1
< 0.1%
732 1
< 0.1%

V124
Real number (ℝ)

SKEWED  ZEROS 

Distinct253
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.272972863
Minimum0
Maximum9209
Zeros47950
Zeros (%)65.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:38.689134image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile25
Maximum9209
Range9209
Interquartile range (IQR)3

Descriptive statistics

Standard deviation44.03822796
Coefficient of variation (CV)8.351688716
Kurtosis26966.87216
Mean5.272972863
Median Absolute Deviation (MAD)0
Skewness140.4079598
Sum388423
Variance1939.365522
MonotonicityNot monotonic
2024-03-09T21:11:38.968090image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47950
65.1%
1 3156
 
4.3%
2 2654
 
3.6%
3 2184
 
3.0%
4 1828
 
2.5%
5 1527
 
2.1%
6 1366
 
1.9%
7 1210
 
1.6%
8 1008
 
1.4%
9 878
 
1.2%
Other values (243) 9902
 
13.4%
ValueCountFrequency (%)
0 47950
65.1%
1 3156
 
4.3%
2 2654
 
3.6%
3 2184
 
3.0%
4 1828
 
2.5%
ValueCountFrequency (%)
9209 1
< 0.1%
3631 1
< 0.1%
2988 1
< 0.1%
1845 1
< 0.1%
1821 1
< 0.1%

V125
Real number (ℝ)

SKEWED  ZEROS 

Distinct26
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0321735471
Minimum0
Maximum151
Zeros72863
Zeros (%)98.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:39.203614image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum151
Range151
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8625324744
Coefficient of variation (CV)26.80874669
Kurtosis17543.7298
Mean0.0321735471
Median Absolute Deviation (MAD)0
Skewness116.0527116
Sum2370
Variance0.7439622695
MonotonicityNot monotonic
2024-03-09T21:11:39.444034image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 72863
98.9%
1 461
 
0.6%
2 122
 
0.2%
3 65
 
0.1%
4 45
 
0.1%
5 24
 
< 0.1%
6 20
 
< 0.1%
7 12
 
< 0.1%
10 9
 
< 0.1%
9 7
 
< 0.1%
Other values (16) 35
 
< 0.1%
ValueCountFrequency (%)
0 72863
98.9%
1 461
 
0.6%
2 122
 
0.2%
3 65
 
0.1%
4 45
 
0.1%
ValueCountFrequency (%)
151 1
< 0.1%
112 1
< 0.1%
77 1
< 0.1%
31 1
< 0.1%
29 1
< 0.1%

V126
Real number (ℝ)

SKEWED  ZEROS 

Distinct49
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.116204879
Minimum0
Maximum212
Zeros72142
Zeros (%)97.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:39.713138image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum212
Range212
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.566250679
Coefficient of variation (CV)13.47835558
Kurtosis5240.571004
Mean0.116204879
Median Absolute Deviation (MAD)0
Skewness51.69694843
Sum8560
Variance2.453141189
MonotonicityNot monotonic
2024-03-09T21:11:39.980521image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0 72142
97.9%
1 439
 
0.6%
2 234
 
0.3%
3 167
 
0.2%
4 111
 
0.2%
5 110
 
0.1%
6 86
 
0.1%
7 62
 
0.1%
8 42
 
0.1%
9 40
 
0.1%
Other values (39) 230
 
0.3%
ValueCountFrequency (%)
0 72142
97.9%
1 439
 
0.6%
2 234
 
0.3%
3 167
 
0.2%
4 111
 
0.2%
ValueCountFrequency (%)
212 1
< 0.1%
97 1
< 0.1%
94 1
< 0.1%
69 1
< 0.1%
65 1
< 0.1%

V127
Real number (ℝ)

SKEWED  ZEROS 

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03255365652
Minimum0
Maximum53
Zeros72319
Zeros (%)98.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:40.200569image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum53
Range53
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4107832238
Coefficient of variation (CV)12.6186508
Kurtosis5052.473628
Mean0.03255365652
Median Absolute Deviation (MAD)0
Skewness52.62403919
Sum2398
Variance0.168742857
MonotonicityNot monotonic
2024-03-09T21:11:40.424669image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 72319
98.2%
1 917
 
1.2%
2 241
 
0.3%
3 79
 
0.1%
4 41
 
0.1%
5 27
 
< 0.1%
8 7
 
< 0.1%
7 7
 
< 0.1%
6 6
 
< 0.1%
9 3
 
< 0.1%
Other values (10) 16
 
< 0.1%
ValueCountFrequency (%)
0 72319
98.2%
1 917
 
1.2%
2 241
 
0.3%
3 79
 
0.1%
4 41
 
0.1%
ValueCountFrequency (%)
53 1
< 0.1%
36 1
< 0.1%
24 1
< 0.1%
18 2
< 0.1%
17 2
< 0.1%

V128
Real number (ℝ)

SKEWED  ZEROS 

Distinct133
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.97598523
Minimum0
Maximum976
Zeros55291
Zeros (%)75.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:40.713401image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile11
Maximum976
Range976
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.02090381
Coefficient of variation (CV)5.071345503
Kurtosis4197.826928
Mean1.97598523
Median Absolute Deviation (MAD)0
Skewness50.8004828
Sum145557
Variance100.4185132
MonotonicityNot monotonic
2024-03-09T21:11:40.998450image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 55291
75.1%
1 3572
 
4.8%
2 2618
 
3.6%
3 1981
 
2.7%
4 1547
 
2.1%
5 1190
 
1.6%
6 1041
 
1.4%
7 806
 
1.1%
8 699
 
0.9%
9 586
 
0.8%
Other values (123) 4332
 
5.9%
ValueCountFrequency (%)
0 55291
75.1%
1 3572
 
4.8%
2 2618
 
3.6%
3 1981
 
2.7%
4 1547
 
2.1%
ValueCountFrequency (%)
976 1
< 0.1%
927 1
< 0.1%
850 1
< 0.1%
822 1
< 0.1%
810 1
< 0.1%

V129
Real number (ℝ)

SKEWED  ZEROS 

Distinct133
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.494943187
Minimum0
Maximum770
Zeros57933
Zeros (%)78.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:41.256031image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile8
Maximum770
Range770
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.461940361
Coefficient of variation (CV)5.660375881
Kurtosis2906.323306
Mean1.494943187
Median Absolute Deviation (MAD)0
Skewness41.1390851
Sum110122
Variance71.60443467
MonotonicityNot monotonic
2024-03-09T21:11:41.539732image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 57933
78.6%
1 3964
 
5.4%
2 2626
 
3.6%
3 1761
 
2.4%
4 1283
 
1.7%
5 961
 
1.3%
6 721
 
1.0%
7 624
 
0.8%
8 468
 
0.6%
9 390
 
0.5%
Other values (123) 2932
 
4.0%
ValueCountFrequency (%)
0 57933
78.6%
1 3964
 
5.4%
2 2626
 
3.6%
3 1761
 
2.4%
4 1283
 
1.7%
ValueCountFrequency (%)
770 1
< 0.1%
722 1
< 0.1%
672 1
< 0.1%
608 1
< 0.1%
472 1
< 0.1%

V130
Real number (ℝ)

SKEWED  ZEROS 

Distinct205
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.470928417
Minimum0
Maximum1698
Zeros53686
Zeros (%)72.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:41.822719image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile18
Maximum1698
Range1698
Interquartile range (IQR)1

Descriptive statistics

Standard deviation18.12368978
Coefficient of variation (CV)5.221568297
Kurtosis3740.494427
Mean3.470928417
Median Absolute Deviation (MAD)0
Skewness47.39155785
Sum255679
Variance328.4681314
MonotonicityNot monotonic
2024-03-09T21:11:42.157180image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 53686
72.9%
1 2850
 
3.9%
2 2178
 
3.0%
3 1756
 
2.4%
4 1513
 
2.1%
5 1228
 
1.7%
6 1058
 
1.4%
7 862
 
1.2%
8 746
 
1.0%
9 659
 
0.9%
Other values (195) 7127
 
9.7%
ValueCountFrequency (%)
0 53686
72.9%
1 2850
 
3.9%
2 2178
 
3.0%
3 1756
 
2.4%
4 1513
 
2.1%
ValueCountFrequency (%)
1698 1
< 0.1%
1697 1
< 0.1%
1522 1
< 0.1%
1430 1
< 0.1%
1282 1
< 0.1%

V131
Real number (ℝ)

SKEWED  ZEROS 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01926340225
Minimum0
Maximum37
Zeros73080
Zeros (%)99.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:42.408128image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum37
Range37
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3405652706
Coefficient of variation (CV)17.67939361
Kurtosis2724.457025
Mean0.01926340225
Median Absolute Deviation (MAD)0
Skewness40.37904456
Sum1419
Variance0.1159847035
MonotonicityNot monotonic
2024-03-09T21:11:42.622206image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 73080
99.2%
1 332
 
0.5%
2 89
 
0.1%
3 56
 
0.1%
4 39
 
0.1%
5 17
 
< 0.1%
7 13
 
< 0.1%
6 8
 
< 0.1%
8 6
 
< 0.1%
9 4
 
< 0.1%
Other values (8) 19
 
< 0.1%
ValueCountFrequency (%)
0 73080
99.2%
1 332
 
0.5%
2 89
 
0.1%
3 56
 
0.1%
4 39
 
0.1%
ValueCountFrequency (%)
37 1
 
< 0.1%
20 1
 
< 0.1%
16 2
< 0.1%
15 4
< 0.1%
14 3
< 0.1%

V132
Real number (ℝ)

SKEWED  ZEROS 

Distinct41
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07450144577
Minimum0
Maximum73
Zeros72518
Zeros (%)98.4%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:42.872996image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum73
Range73
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9897737831
Coefficient of variation (CV)13.28529632
Kurtosis1237.658066
Mean0.07450144577
Median Absolute Deviation (MAD)0
Skewness28.48076814
Sum5488
Variance0.9796521418
MonotonicityNot monotonic
2024-03-09T21:11:43.139973image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 72518
98.4%
1 354
 
0.5%
2 209
 
0.3%
3 113
 
0.2%
4 99
 
0.1%
5 70
 
0.1%
6 57
 
0.1%
7 38
 
0.1%
8 32
 
< 0.1%
9 23
 
< 0.1%
Other values (31) 150
 
0.2%
ValueCountFrequency (%)
0 72518
98.4%
1 354
 
0.5%
2 209
 
0.3%
3 113
 
0.2%
4 99
 
0.1%
ValueCountFrequency (%)
73 1
< 0.1%
55 1
< 0.1%
53 1
< 0.1%
51 1
< 0.1%
50 1
< 0.1%

V133
Real number (ℝ)

SKEWED  ZEROS 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02153048342
Minimum0
Maximum21
Zeros72743
Zeros (%)98.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:43.372455image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum21
Range21
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2816617514
Coefficient of variation (CV)13.08199848
Kurtosis1391.903745
Mean0.02153048342
Median Absolute Deviation (MAD)0
Skewness30.19165243
Sum1586
Variance0.0793333422
MonotonicityNot monotonic
2024-03-09T21:11:43.586572image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 72743
98.8%
1 639
 
0.9%
2 158
 
0.2%
3 50
 
0.1%
4 33
 
< 0.1%
5 11
 
< 0.1%
8 8
 
< 0.1%
7 4
 
< 0.1%
9 3
 
< 0.1%
13 3
 
< 0.1%
Other values (8) 11
 
< 0.1%
ValueCountFrequency (%)
0 72743
98.8%
1 639
 
0.9%
2 158
 
0.2%
3 50
 
0.1%
4 33
 
< 0.1%
ValueCountFrequency (%)
21 1
 
< 0.1%
18 1
 
< 0.1%
16 1
 
< 0.1%
14 1
 
< 0.1%
13 3
< 0.1%

V134
Real number (ℝ)

SKEWED  ZEROS 

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001547588342
Minimum0
Maximum45
Zeros73652
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:43.775181image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum45
Range45
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2143929051
Coefficient of variation (CV)138.5335489
Kurtosis34219.75021
Mean0.001547588342
Median Absolute Deviation (MAD)0
Skewness179.2318921
Sum114
Variance0.04596431776
MonotonicityNot monotonic
2024-03-09T21:11:44.772306image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 73652
> 99.9%
2 4
 
< 0.1%
5 2
 
< 0.1%
45 1
 
< 0.1%
33 1
 
< 0.1%
3 1
 
< 0.1%
14 1
 
< 0.1%
1 1
 
< 0.1%
ValueCountFrequency (%)
0 73652
> 99.9%
1 1
 
< 0.1%
2 4
 
< 0.1%
3 1
 
< 0.1%
5 2
 
< 0.1%
ValueCountFrequency (%)
45 1
< 0.1%
33 1
< 0.1%
14 1
< 0.1%
5 2
< 0.1%
3 1
< 0.1%

V135
Real number (ℝ)

SKEWED  ZEROS 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0003665340809
Minimum0
Maximum8
Zeros73655
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:44.952330image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04216940659
Coefficient of variation (CV)115.049074
Kurtosis22605.43841
Mean0.0003665340809
Median Absolute Deviation (MAD)0
Skewness141.7286591
Sum27
Variance0.001778258852
MonotonicityNot monotonic
2024-03-09T21:11:45.156579image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 73655
> 99.9%
1 2
 
< 0.1%
4 2
 
< 0.1%
2 2
 
< 0.1%
8 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
0 73655
> 99.9%
1 2
 
< 0.1%
2 2
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
8 1
< 0.1%
5 1
< 0.1%
4 2
< 0.1%
2 2
< 0.1%
1 2
< 0.1%

V136
Real number (ℝ)

SKEWED  ZEROS 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001914122422
Minimum0
Maximum45
Zeros73651
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:45.355608image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum45
Range45
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2376066631
Coefficient of variation (CV)124.1334725
Kurtosis29801.0382
Mean0.001914122422
Median Absolute Deviation (MAD)0
Skewness167.2002678
Sum141
Variance0.05645692635
MonotonicityNot monotonic
2024-03-09T21:11:45.540458image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 73651
> 99.9%
3 2
 
< 0.1%
2 2
 
< 0.1%
6 2
 
< 0.1%
5 2
 
< 0.1%
45 1
 
< 0.1%
41 1
 
< 0.1%
7 1
 
< 0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
0 73651
> 99.9%
2 2
 
< 0.1%
3 2
 
< 0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
ValueCountFrequency (%)
45 1
< 0.1%
41 1
< 0.1%
16 1
< 0.1%
7 1
< 0.1%
6 2
< 0.1%

V137
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros73663
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:45.713787image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2024-03-09T21:11:45.902508image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 73663
100.0%
ValueCountFrequency (%)
0 73663
100.0%
ValueCountFrequency (%)
0 73663
100.0%

V138
Real number (ℝ)

SKEWED  ZEROS 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0002443560539
Minimum0
Maximum16
Zeros73661
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:46.090622image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05941023187
Coefficient of variation (CV)243.1297728
Kurtosis71431.21041
Mean0.0002443560539
Median Absolute Deviation (MAD)0
Skewness265.6878691
Sum18
Variance0.003529575651
MonotonicityNot monotonic
2024-03-09T21:11:46.278866image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 73661
> 99.9%
2 1
 
< 0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
0 73661
> 99.9%
2 1
 
< 0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
16 1
 
< 0.1%
2 1
 
< 0.1%
0 73661
> 99.9%

V139
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros73663
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:46.489172image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2024-03-09T21:11:46.679410image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 73663
100.0%
ValueCountFrequency (%)
0 73663
100.0%
ValueCountFrequency (%)
0 73663
100.0%

V140
Real number (ℝ)

SKEWED  ZEROS 

Distinct313
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.051803483
Minimum0
Maximum5094
Zeros44668
Zeros (%)60.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:46.914538image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile40
Maximum5094
Range5094
Interquartile range (IQR)6

Descriptive statistics

Standard deviation36.26047625
Coefficient of variation (CV)4.503398068
Kurtosis6513.338605
Mean8.051803483
Median Absolute Deviation (MAD)0
Skewness60.18857148
Sum593120
Variance1314.822138
MonotonicityNot monotonic
2024-03-09T21:11:47.197562image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44668
60.6%
1 2676
 
3.6%
2 2205
 
3.0%
3 1867
 
2.5%
4 1631
 
2.2%
5 1483
 
2.0%
6 1338
 
1.8%
7 1185
 
1.6%
8 1064
 
1.4%
9 971
 
1.3%
Other values (303) 14575
 
19.8%
ValueCountFrequency (%)
0 44668
60.6%
1 2676
 
3.6%
2 2205
 
3.0%
3 1867
 
2.5%
4 1631
 
2.2%
ValueCountFrequency (%)
5094 1
< 0.1%
2381 1
< 0.1%
2339 1
< 0.1%
2296 1
< 0.1%
2136 1
< 0.1%

V141
Real number (ℝ)

SKEWED  ZEROS 

Distinct301
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.364049794
Minimum0
Maximum5949
Zeros46834
Zeros (%)63.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:47.467906image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile31
Maximum5949
Range5949
Interquartile range (IQR)4

Descriptive statistics

Standard deviation36.61645709
Coefficient of variation (CV)5.753640885
Kurtosis11197.33253
Mean6.364049794
Median Absolute Deviation (MAD)0
Skewness82.32078966
Sum468795
Variance1340.76493
MonotonicityNot monotonic
2024-03-09T21:11:47.753408image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46834
63.6%
1 3503
 
4.8%
2 2635
 
3.6%
3 2168
 
2.9%
4 1694
 
2.3%
5 1465
 
2.0%
6 1241
 
1.7%
7 1160
 
1.6%
8 955
 
1.3%
9 833
 
1.1%
Other values (291) 11175
 
15.2%
ValueCountFrequency (%)
0 46834
63.6%
1 3503
 
4.8%
2 2635
 
3.6%
3 2168
 
2.9%
4 1694
 
2.3%
ValueCountFrequency (%)
5949 1
< 0.1%
3578 1
< 0.1%
2548 1
< 0.1%
1747 1
< 0.1%
1622 1
< 0.1%

V142
Real number (ℝ)

SKEWED  ZEROS 

Distinct489
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.41585328
Minimum0
Maximum11043
Zeros43485
Zeros (%)59.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:48.036551image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q310
95-th percentile70
Maximum11043
Range11043
Interquartile range (IQR)10

Descriptive statistics

Standard deviation71.78326871
Coefficient of variation (CV)4.97946721
Kurtosis8811.600881
Mean14.41585328
Median Absolute Deviation (MAD)0
Skewness70.88176582
Sum1061915
Variance5152.837666
MonotonicityNot monotonic
2024-03-09T21:11:48.325459image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43485
59.0%
1 1989
 
2.7%
2 1634
 
2.2%
3 1378
 
1.9%
4 1294
 
1.8%
5 1194
 
1.6%
6 1063
 
1.4%
7 985
 
1.3%
8 967
 
1.3%
9 892
 
1.2%
Other values (479) 18782
25.5%
ValueCountFrequency (%)
0 43485
59.0%
1 1989
 
2.7%
2 1634
 
2.2%
3 1378
 
1.9%
4 1294
 
1.8%
ValueCountFrequency (%)
11043 1
< 0.1%
5714 1
< 0.1%
4276 1
< 0.1%
4043 1
< 0.1%
4003 1
< 0.1%

V143
Real number (ℝ)

SKEWED  ZEROS 

Distinct47
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09008593188
Minimum0
Maximum250
Zeros72085
Zeros (%)97.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:48.611647image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum250
Range250
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.606475443
Coefficient of variation (CV)17.8327005
Kurtosis10332.55998
Mean0.09008593188
Median Absolute Deviation (MAD)0
Skewness80.48784059
Sum6636
Variance2.580763348
MonotonicityNot monotonic
2024-03-09T21:11:48.900633image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 72085
97.9%
1 774
 
1.1%
2 274
 
0.4%
3 130
 
0.2%
4 74
 
0.1%
5 52
 
0.1%
7 35
 
< 0.1%
9 32
 
< 0.1%
6 30
 
< 0.1%
8 26
 
< 0.1%
Other values (37) 151
 
0.2%
ValueCountFrequency (%)
0 72085
97.9%
1 774
 
1.1%
2 274
 
0.4%
3 130
 
0.2%
4 74
 
0.1%
ValueCountFrequency (%)
250 1
< 0.1%
178 1
< 0.1%
79 1
< 0.1%
77 1
< 0.1%
61 1
< 0.1%

V144
Real number (ℝ)

SKEWED  ZEROS 

Distinct97
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3170791306
Minimum0
Maximum331
Zeros71505
Zeros (%)97.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:49.167491image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum331
Range331
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.688678679
Coefficient of variation (CV)11.6333064
Kurtosis1781.910021
Mean0.3170791306
Median Absolute Deviation (MAD)0
Skewness32.21362872
Sum23357
Variance13.60635039
MonotonicityNot monotonic
2024-03-09T21:11:49.439206image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71505
97.1%
1 468
 
0.6%
2 253
 
0.3%
3 193
 
0.3%
4 142
 
0.2%
6 89
 
0.1%
8 89
 
0.1%
7 88
 
0.1%
5 85
 
0.1%
9 66
 
0.1%
Other values (87) 685
 
0.9%
ValueCountFrequency (%)
0 71505
97.1%
1 468
 
0.6%
2 253
 
0.3%
3 193
 
0.3%
4 142
 
0.2%
ValueCountFrequency (%)
331 1
< 0.1%
240 1
< 0.1%
238 1
< 0.1%
187 1
< 0.1%
142 2
< 0.1%

V145
Real number (ℝ)

SKEWED  ZEROS 

Distinct38
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0925973691
Minimum0
Maximum83
Zeros70908
Zeros (%)96.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:49.707870image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum83
Range83
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8849806213
Coefficient of variation (CV)9.557297684
Kurtosis1941.593483
Mean0.0925973691
Median Absolute Deviation (MAD)0
Skewness32.96285914
Sum6821
Variance0.7831907
MonotonicityNot monotonic
2024-03-09T21:11:49.943258image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 70908
96.3%
1 1546
 
2.1%
2 535
 
0.7%
3 240
 
0.3%
4 132
 
0.2%
5 75
 
0.1%
6 55
 
0.1%
7 37
 
0.1%
8 32
 
< 0.1%
9 21
 
< 0.1%
Other values (28) 82
 
0.1%
ValueCountFrequency (%)
0 70908
96.3%
1 1546
 
2.1%
2 535
 
0.7%
3 240
 
0.3%
4 132
 
0.2%
ValueCountFrequency (%)
83 1
< 0.1%
63 1
< 0.1%
52 1
< 0.1%
37 2
< 0.1%
35 1
< 0.1%

V146
Real number (ℝ)

ZEROS 

Distinct299
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.665720918
Minimum0
Maximum1133
Zeros30469
Zeros (%)41.4%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:50.195096image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q37
95-th percentile33
Maximum1133
Range1133
Interquartile range (IQR)7

Descriptive statistics

Standard deviation25.41904209
Coefficient of variation (CV)3.315936279
Kurtosis548.7388179
Mean7.665720918
Median Absolute Deviation (MAD)1
Skewness18.3770661
Sum564680
Variance646.127701
MonotonicityNot monotonic
2024-03-09T21:11:50.455456image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30469
41.4%
1 6778
 
9.2%
2 5192
 
7.0%
3 3887
 
5.3%
4 3221
 
4.4%
5 2731
 
3.7%
6 2186
 
3.0%
7 1792
 
2.4%
8 1666
 
2.3%
10 1295
 
1.8%
Other values (289) 14446
19.6%
ValueCountFrequency (%)
0 30469
41.4%
1 6778
 
9.2%
2 5192
 
7.0%
3 3887
 
5.3%
4 3221
 
4.4%
ValueCountFrequency (%)
1133 1
< 0.1%
1100 1
< 0.1%
1061 1
< 0.1%
1025 1
< 0.1%
1002 1
< 0.1%

V147
Real number (ℝ)

ZEROS 

Distinct361
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.910280602
Minimum0
Maximum1658
Zeros28989
Zeros (%)39.4%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:50.736781image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q38
95-th percentile44
Maximum1658
Range1658
Interquartile range (IQR)8

Descriptive statistics

Standard deviation32.7600566
Coefficient of variation (CV)3.305663878
Kurtosis543.1573948
Mean9.910280602
Median Absolute Deviation (MAD)2
Skewness17.74901293
Sum730021
Variance1073.221309
MonotonicityNot monotonic
2024-03-09T21:11:51.022742image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28989
39.4%
1 6195
 
8.4%
2 4861
 
6.6%
3 3790
 
5.1%
4 3087
 
4.2%
5 2683
 
3.6%
6 2160
 
2.9%
7 1878
 
2.5%
8 1660
 
2.3%
9 1428
 
1.9%
Other values (351) 16932
23.0%
ValueCountFrequency (%)
0 28989
39.4%
1 6195
 
8.4%
2 4861
 
6.6%
3 3790
 
5.1%
4 3087
 
4.2%
ValueCountFrequency (%)
1658 1
< 0.1%
1424 1
< 0.1%
1405 1
< 0.1%
1376 1
< 0.1%
1360 1
< 0.1%

V148
Real number (ℝ)

ZEROS 

Distinct516
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.57600152
Minimum0
Maximum2758
Zeros25690
Zeros (%)34.9%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:51.292533image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q315
95-th percentile76
Maximum2758
Range2758
Interquartile range (IQR)15

Descriptive statistics

Standard deviation57.75336433
Coefficient of variation (CV)3.285921673
Kurtosis549.110399
Mean17.57600152
Median Absolute Deviation (MAD)4
Skewness18.13851177
Sum1294701
Variance3335.451091
MonotonicityNot monotonic
2024-03-09T21:11:51.563807image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25690
34.9%
1 4199
 
5.7%
2 3592
 
4.9%
3 3090
 
4.2%
4 2630
 
3.6%
5 2434
 
3.3%
6 2038
 
2.8%
7 1854
 
2.5%
8 1636
 
2.2%
9 1455
 
2.0%
Other values (506) 25045
34.0%
ValueCountFrequency (%)
0 25690
34.9%
1 4199
 
5.7%
2 3592
 
4.9%
3 3090
 
4.2%
4 2630
 
3.6%
ValueCountFrequency (%)
2758 1
< 0.1%
2557 1
< 0.1%
2466 1
< 0.1%
2371 1
< 0.1%
2318 1
< 0.1%

V149
Real number (ℝ)

SKEWED  ZEROS 

Distinct56
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09721298345
Minimum0
Maximum162
Zeros72027
Zeros (%)97.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:51.831071image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum162
Range162
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.57875813
Coefficient of variation (CV)16.24019831
Kurtosis2995.376857
Mean0.09721298345
Median Absolute Deviation (MAD)0
Skewness44.30923617
Sum7161
Variance2.492477231
MonotonicityNot monotonic
2024-03-09T21:11:52.098381image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 72027
97.8%
1 875
 
1.2%
2 250
 
0.3%
3 109
 
0.1%
4 74
 
0.1%
5 51
 
0.1%
6 35
 
< 0.1%
7 29
 
< 0.1%
10 23
 
< 0.1%
8 21
 
< 0.1%
Other values (46) 169
 
0.2%
ValueCountFrequency (%)
0 72027
97.8%
1 875
 
1.2%
2 250
 
0.3%
3 109
 
0.1%
4 74
 
0.1%
ValueCountFrequency (%)
162 1
< 0.1%
130 1
< 0.1%
91 2
< 0.1%
85 1
< 0.1%
73 2
< 0.1%

V150
Real number (ℝ)

ZEROS 

Distinct116
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6578336478
Minimum0
Maximum254
Zeros69442
Zeros (%)94.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:52.388977image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum254
Range254
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.109132776
Coefficient of variation (CV)7.76660299
Kurtosis515.7310399
Mean0.6578336478
Median Absolute Deviation (MAD)0
Skewness18.19264207
Sum48458
Variance26.10323772
MonotonicityNot monotonic
2024-03-09T21:11:52.653818image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 69442
94.3%
1 791
 
1.1%
2 466
 
0.6%
3 335
 
0.5%
4 269
 
0.4%
5 222
 
0.3%
6 178
 
0.2%
7 168
 
0.2%
8 152
 
0.2%
9 143
 
0.2%
Other values (106) 1497
 
2.0%
ValueCountFrequency (%)
0 69442
94.3%
1 791
 
1.1%
2 466
 
0.6%
3 335
 
0.5%
4 269
 
0.4%
ValueCountFrequency (%)
254 1
< 0.1%
240 1
< 0.1%
222 1
< 0.1%
200 1
< 0.1%
189 2
< 0.1%

V151
Real number (ℝ)

SKEWED  ZEROS 

Distinct33
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1177931933
Minimum0
Maximum64
Zeros69792
Zeros (%)94.7%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:52.910893image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum64
Range64
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9147272658
Coefficient of variation (CV)7.765535851
Kurtosis1536.814633
Mean0.1177931933
Median Absolute Deviation (MAD)0
Skewness29.72425342
Sum8677
Variance0.8367259708
MonotonicityNot monotonic
2024-03-09T21:11:53.146522image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 69792
94.7%
1 2267
 
3.1%
2 748
 
1.0%
3 317
 
0.4%
4 180
 
0.2%
5 106
 
0.1%
6 71
 
0.1%
7 42
 
0.1%
8 29
 
< 0.1%
9 24
 
< 0.1%
Other values (23) 87
 
0.1%
ValueCountFrequency (%)
0 69792
94.7%
1 2267
 
3.1%
2 748
 
1.0%
3 317
 
0.4%
4 180
 
0.2%
ValueCountFrequency (%)
64 1
< 0.1%
63 1
< 0.1%
58 1
< 0.1%
57 2
< 0.1%
44 1
< 0.1%

V152
Real number (ℝ)

ZEROS 

Distinct294
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.06160488
Minimum0
Maximum1088
Zeros18972
Zeros (%)25.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:53.405590image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q39
95-th percentile45
Maximum1088
Range1088
Interquartile range (IQR)9

Descriptive statistics

Standard deviation23.94569316
Coefficient of variation (CV)2.379907923
Kurtosis293.1942752
Mean10.06160488
Median Absolute Deviation (MAD)3
Skewness11.62682169
Sum741168
Variance573.3962211
MonotonicityNot monotonic
2024-03-09T21:11:53.670942image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18972
25.8%
1 6936
 
9.4%
2 6620
 
9.0%
3 5524
 
7.5%
4 4416
 
6.0%
5 3786
 
5.1%
6 2919
 
4.0%
7 2372
 
3.2%
8 2079
 
2.8%
9 1682
 
2.3%
Other values (284) 18357
24.9%
ValueCountFrequency (%)
0 18972
25.8%
1 6936
 
9.4%
2 6620
 
9.0%
3 5524
 
7.5%
4 4416
 
6.0%
ValueCountFrequency (%)
1088 1
< 0.1%
966 1
< 0.1%
889 1
< 0.1%
869 1
< 0.1%
808 1
< 0.1%

V153
Real number (ℝ)

ZEROS 

Distinct356
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.51100281
Minimum0
Maximum1076
Zeros19324
Zeros (%)26.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:53.938323image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q310
95-th percentile59
Maximum1076
Range1076
Interquartile range (IQR)10

Descriptive statistics

Standard deviation31.69970015
Coefficient of variation (CV)2.533745746
Kurtosis209.1741935
Mean12.51100281
Median Absolute Deviation (MAD)3
Skewness10.2158457
Sum921598
Variance1004.87099
MonotonicityNot monotonic
2024-03-09T21:11:54.221169image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 19324
26.2%
1 6691
 
9.1%
2 6106
 
8.3%
3 5172
 
7.0%
4 4230
 
5.7%
5 3544
 
4.8%
6 2818
 
3.8%
7 2330
 
3.2%
8 2009
 
2.7%
9 1561
 
2.1%
Other values (346) 19878
27.0%
ValueCountFrequency (%)
0 19324
26.2%
1 6691
 
9.1%
2 6106
 
8.3%
3 5172
 
7.0%
4 4230
 
5.7%
ValueCountFrequency (%)
1076 1
< 0.1%
1060 1
< 0.1%
1042 1
< 0.1%
1031 1
< 0.1%
992 1
< 0.1%

V154
Real number (ℝ)

ZEROS 

Distinct520
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.57260769
Minimum0
Maximum2080
Zeros15185
Zeros (%)20.6%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:54.477759image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q320
95-th percentile103
Maximum2080
Range2080
Interquartile range (IQR)19

Descriptive statistics

Standard deviation54.98036622
Coefficient of variation (CV)2.43571177
Kurtosis238.9246576
Mean22.57260769
Median Absolute Deviation (MAD)7
Skewness10.75286161
Sum1662766
Variance3022.84067
MonotonicityNot monotonic
2024-03-09T21:11:54.739172image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15185
20.6%
3 3721
 
5.1%
2 3642
 
4.9%
4 3597
 
4.9%
1 3366
 
4.6%
5 3260
 
4.4%
6 2889
 
3.9%
7 2618
 
3.6%
8 2409
 
3.3%
9 2186
 
3.0%
Other values (510) 30790
41.8%
ValueCountFrequency (%)
0 15185
20.6%
1 3366
 
4.6%
2 3642
 
4.9%
3 3721
 
5.1%
4 3597
 
4.9%
ValueCountFrequency (%)
2080 1
< 0.1%
1945 1
< 0.1%
1868 1
< 0.1%
1859 1
< 0.1%
1840 1
< 0.1%

V155
Real number (ℝ)

SKEWED  ZEROS 

Distinct70
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1655783772
Minimum0
Maximum402
Zeros71286
Zeros (%)96.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:54.987575image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum402
Range402
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.750416035
Coefficient of variation (CV)16.61096141
Kurtosis9037.464286
Mean0.1655783772
Median Absolute Deviation (MAD)0
Skewness74.42833409
Sum12197
Variance7.564788365
MonotonicityNot monotonic
2024-03-09T21:11:55.270107image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 71286
96.8%
1 1200
 
1.6%
2 381
 
0.5%
3 176
 
0.2%
4 106
 
0.1%
5 80
 
0.1%
6 77
 
0.1%
10 35
 
< 0.1%
7 34
 
< 0.1%
9 24
 
< 0.1%
Other values (60) 264
 
0.4%
ValueCountFrequency (%)
0 71286
96.8%
1 1200
 
1.6%
2 381
 
0.5%
3 176
 
0.2%
4 106
 
0.1%
ValueCountFrequency (%)
402 1
< 0.1%
324 1
< 0.1%
110 1
< 0.1%
91 1
< 0.1%
90 1
< 0.1%

V156
Real number (ℝ)

ZEROS 

Distinct91
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7495350447
Minimum0
Maximum147
Zeros67956
Zeros (%)92.3%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:55.543308image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum147
Range147
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.237589901
Coefficient of variation (CV)5.653624778
Kurtosis190.7733663
Mean0.7495350447
Median Absolute Deviation (MAD)0
Skewness11.08041005
Sum55213
Variance17.95716817
MonotonicityNot monotonic
2024-03-09T21:11:55.810226image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 67956
92.3%
1 890
 
1.2%
2 602
 
0.8%
3 500
 
0.7%
4 420
 
0.6%
5 382
 
0.5%
6 301
 
0.4%
7 273
 
0.4%
8 237
 
0.3%
9 198
 
0.3%
Other values (81) 1904
 
2.6%
ValueCountFrequency (%)
0 67956
92.3%
1 890
 
1.2%
2 602
 
0.8%
3 500
 
0.7%
4 420
 
0.6%
ValueCountFrequency (%)
147 1
< 0.1%
144 1
< 0.1%
136 1
< 0.1%
132 1
< 0.1%
118 1
< 0.1%

V157
Real number (ℝ)

SKEWED  ZEROS 

Distinct47
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1821402875
Minimum0
Maximum217
Zeros68507
Zeros (%)93.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:56.084160image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum217
Range217
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.666432705
Coefficient of variation (CV)9.149171376
Kurtosis6004.09776
Mean0.1821402875
Median Absolute Deviation (MAD)0
Skewness59.10580381
Sum13417
Variance2.77699796
MonotonicityNot monotonic
2024-03-09T21:11:56.339036image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 68507
93.0%
1 2930
 
4.0%
2 985
 
1.3%
3 427
 
0.6%
4 254
 
0.3%
5 173
 
0.2%
6 79
 
0.1%
7 49
 
0.1%
8 43
 
0.1%
9 29
 
< 0.1%
Other values (37) 187
 
0.3%
ValueCountFrequency (%)
0 68507
93.0%
1 2930
 
4.0%
2 985
 
1.3%
3 427
 
0.6%
4 254
 
0.3%
ValueCountFrequency (%)
217 1
< 0.1%
154 1
< 0.1%
152 1
< 0.1%
64 2
< 0.1%
58 1
< 0.1%

V158
Real number (ℝ)

SKEWED  ZEROS 

Distinct193
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.322183457
Minimum0
Maximum954
Zeros35409
Zeros (%)48.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:56.602944image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile13
Maximum954
Range954
Interquartile range (IQR)3

Descriptive statistics

Standard deviation13.96293272
Coefficient of variation (CV)4.202938491
Kurtosis1406.767739
Mean3.322183457
Median Absolute Deviation (MAD)1
Skewness28.54705464
Sum244722
Variance194.9634903
MonotonicityNot monotonic
2024-03-09T21:11:57.653445image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 35409
48.1%
1 11888
 
16.1%
2 7217
 
9.8%
3 4482
 
6.1%
4 2939
 
4.0%
5 2127
 
2.9%
6 1469
 
2.0%
7 1112
 
1.5%
8 938
 
1.3%
9 707
 
1.0%
Other values (183) 5375
 
7.3%
ValueCountFrequency (%)
0 35409
48.1%
1 11888
 
16.1%
2 7217
 
9.8%
3 4482
 
6.1%
4 2939
 
4.0%
ValueCountFrequency (%)
954 1
< 0.1%
869 1
< 0.1%
835 1
< 0.1%
808 1
< 0.1%
798 1
< 0.1%

V159
Real number (ℝ)

SKEWED  ZEROS 

Distinct226
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.29201906
Minimum0
Maximum1076
Zeros38158
Zeros (%)51.8%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:57.936447image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile12
Maximum1076
Range1076
Interquartile range (IQR)2

Descriptive statistics

Standard deviation15.8577775
Coefficient of variation (CV)4.817036965
Kurtosis1530.978679
Mean3.29201906
Median Absolute Deviation (MAD)0
Skewness29.42979686
Sum242500
Variance251.4691072
MonotonicityNot monotonic
2024-03-09T21:11:58.203794image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38158
51.8%
1 12085
 
16.4%
2 6617
 
9.0%
3 3944
 
5.4%
4 2543
 
3.5%
5 1756
 
2.4%
6 1241
 
1.7%
7 973
 
1.3%
8 799
 
1.1%
9 647
 
0.9%
Other values (216) 4900
 
6.7%
ValueCountFrequency (%)
0 38158
51.8%
1 12085
 
16.4%
2 6617
 
9.0%
3 3944
 
5.4%
4 2543
 
3.5%
ValueCountFrequency (%)
1076 1
< 0.1%
1060 1
< 0.1%
1042 1
< 0.1%
1031 1
< 0.1%
984 1
< 0.1%

V160
Real number (ℝ)

SKEWED  ZEROS 

Distinct335
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.614202517
Minimum0
Maximum1945
Zeros28781
Zeros (%)39.1%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:58.491402image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile25
Maximum1945
Range1945
Interquartile range (IQR)5

Descriptive statistics

Standard deviation29.49686447
Coefficient of variation (CV)4.459625237
Kurtosis1464.724974
Mean6.614202517
Median Absolute Deviation (MAD)1
Skewness29.12622102
Sum487222
Variance870.0650135
MonotonicityNot monotonic
2024-03-09T21:11:58.777114image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28781
39.1%
1 9691
 
13.2%
2 7170
 
9.7%
3 5122
 
7.0%
4 3669
 
5.0%
5 2781
 
3.8%
6 2180
 
3.0%
7 1648
 
2.2%
8 1346
 
1.8%
9 1061
 
1.4%
Other values (325) 10214
 
13.9%
ValueCountFrequency (%)
0 28781
39.1%
1 9691
 
13.2%
2 7170
 
9.7%
3 5122
 
7.0%
4 3669
 
5.0%
ValueCountFrequency (%)
1945 1
< 0.1%
1868 1
< 0.1%
1840 1
< 0.1%
1811 1
< 0.1%
1767 1
< 0.1%

V161
Real number (ℝ)

SKEWED  ZEROS 

Distinct46
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07075465295
Minimum0
Maximum104
Zeros72360
Zeros (%)98.2%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:59.047420image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum104
Range104
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.236505596
Coefficient of variation (CV)17.47596157
Kurtosis3064.800212
Mean0.07075465295
Median Absolute Deviation (MAD)0
Skewness47.07820276
Sum5212
Variance1.528946088
MonotonicityNot monotonic
2024-03-09T21:11:59.315090image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 72360
98.2%
1 712
 
1.0%
2 190
 
0.3%
3 83
 
0.1%
4 52
 
0.1%
5 40
 
0.1%
6 37
 
0.1%
7 24
 
< 0.1%
9 21
 
< 0.1%
10 18
 
< 0.1%
Other values (36) 126
 
0.2%
ValueCountFrequency (%)
0 72360
98.2%
1 712
 
1.0%
2 190
 
0.3%
3 83
 
0.1%
4 52
 
0.1%
ValueCountFrequency (%)
104 1
< 0.1%
101 1
< 0.1%
95 1
< 0.1%
91 1
< 0.1%
82 1
< 0.1%

V162
Real number (ℝ)

ZEROS 

Distinct47
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2195267638
Minimum0
Maximum86
Zeros69639
Zeros (%)94.5%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2024-03-09T21:11:59.589830image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum86
Range86
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.501924375
Coefficient of variation (CV)6.841645862
Kurtosis570.8354012
Mean0.2195267638
Median Absolute Deviation (MAD)0
Skewness17.70833933
Sum16171
Variance2.255776828
MonotonicityNot monotonic
2024-03-09T21:11:59.840113image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 69639
94.5%
1 1246
 
1.7%
2 818
 
1.1%
3 488
 
0.7%
4 370
 
0.5%
5 279
 
0.4%
6 185
 
0.3%
7 118
 
0.2%
8 116
 
0.2%
9 73
 
0.1%
Other values (37) 331
 
0.4%
ValueCountFrequency (%)
0 69639
94.5%
1 1246
 
1.7%
2 818
 
1.1%
3 488
 
0.7%
4 370
 
0.5%
ValueCountFrequency (%)
86 1
< 0.1%
81 1
< 0.1%
68 1
< 0.1%
64 1
< 0.1%
54 1
< 0.1%